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在朋友的幫助下:聯盟管理能力商業模式創新對於實現永續發展目標作用

抽象的

隨著全球各國越來越致力於實現聯合國永續發展目標 (SDG),企業預計將透過積極為實現這些永續發展目標做出貢獻來支持各自國家的議程從關係的角度來看,本研究假設企業聯盟管理能力透過商業模式創新實現永續發展目標績效之間存在正相關關係台灣大型企業總部的高級管理人員進行時滯調查得到 1925 份完整答复(來自 31 1 家製造企業的高級管理人員的 1,1 14 份答復和來自 24 5 家服務業公司的高級管理人員的793 份答案)收集了基於這些反應我們發現企業聯盟管理能力可以正向提升SDG績效,( 2)這種直接效應也是透過商業模式創新來調節的( 3) 這些直接效應和中介效應受到商業模式創新的正調節​總的來說,該研究的結果有助於闡明並憑經驗確定有效利用組織間協作外部知識來創新業務並為永續發展目標做出貢獻的能力的重要作用

關鍵字:永續發展目標可持續性表現;聯盟管理能力B商業模式創新;戰略靈活性。

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介紹

永續發展是一個重要概念,世界環境與發展委員會(1987)將永續發展定義為在不損害子孫後代能力的情況下滿足當前需求的能力。它包含經濟繁榮、環境保護和社會福祉的三方目標(Azmat 等,2023)。永續發展目標 (SDG) 是聯合國大會於 2015 年提出的 2030 年議程,透過 17 個全球目標和 169 個子目標來實施這一概念,旨在指導全球政策走向永續的未來(聯合國,2015 年)。這些目標涵蓋環境永續性、社會誠信和經濟成長(Foroudi等人,2022;Gillani等人,2022;van Gestel等人,2023 )。永續發展目標與企業實體的相關性日益增強(Azmat等人,2023 年;Foroudi等人,2022 年;George等人,2016 年;Gupta等人,2021 年。特別, 永續發展目標 8 和永續發展目標 12強調社會和生態創新,直接影響企業(聯合國,2015)。永續發展目標 8 旨在促進永續經濟成長,同時確保獲得優質就業機會(Rai等人,2019 年)。 SDG 12 著重於提高資源效率,建造環境友善工作場所(Filho等人,2022 年)這些目標共同尋求創造鼓勵永續成長、高效資源利用、共同繁榮和公平工作環境的條件(ChamsGarcía- Blandón ,2019)。從企業角度來看,利害關係人對永續發展實踐和環境、社會和治理 (ESG) 報告透明度的需求不斷增長,企業預計將在永續和道德營運的同時為經濟成長做出貢獻(Claudy等人,2016 年;Pereira人,2023;DiwanAmarayil Sreeraman ,2023;Lim等人,2023)。
永續發展是一個重要概念,世界環境與發展委員會(1987)將永續發展定義為在不損害子孫後代能力的情況下滿足當前需求的能力。它包含經濟繁榮、環境保護和社會福祉的三方目標(Azmat 等,2023)。永續發展目標 (SDG) 是聯合國大會於 2015 年提出的 2030 年議程,透過 17 個全球目標和 169 個子目標來實施這一概念,旨在指導全球政策走向永續的未來(聯合國,2015 年)。這些目標涵蓋環境永續性、社會誠信和經濟成長(Foroudi等人,2022;Gillani等人,2022;van Gestel等人,2023 )。永續發展目標與企業實體的相關性日益增強(Azmat等人,2023 年;Foroudi等人,2022 年;George等人,2016 年;Gupta等人,2021 年。特別,永續發展目標 8 和永續發展目標 12強調社會和生態創新,直接影響企業(聯合國,2015)。永續發展目標 8 旨在促進永續經濟成長,同時確保獲得優質就業機會(Rai等人,2019 年)。SDG 12 著重於提高資源效率,建造環境友善工作場所(Filho等人,2022 年)這些目標共同尋求創造鼓勵永續成長、高效資源利用、共同繁榮和公平工作環境的條件(ChamsGarcía- Blandón ,2019)。從企業角度來看,利害關係人對永續發展實踐和環境、社會和治理 (ESG) 報告透明度的需求不斷增長,企業預計將在永續和道德營運的同時為經濟成長做出貢獻(Claudy等人,2016 年;Pereira人,2023;DiwanAmarayil Sreeraman ,2023;Lim等人,2023)。

儘管人們對永續發展目標做出了廣泛的承諾,越來越多的關於企業對這些目標的貢獻的研究證明了這一點(例如,Al LawatiHussainey ,2022 年;Bradley等人,2021 年; de Ruyter等人,2022 年;EmmaJennifer,2021 年);Gillani等人,2022 ),實際進展仍然有限。約 72% 的公司公開宣稱致力於實現永續發展目標,但只有1% 的公司在實現這些目標方面取得了實質進展(普華永道,2019 年),其中許多公司進展緩慢(Yahya等人,2021 年)。事實上,許多公司優先考慮短期財務利益,與長期永續發展目標衝突。這種短期關注往往會導致資源從永續發展投資中轉移,企業更傾向於眼前收益而不是長期永續發展獎勵(《金融時報》,2024年;Kim等人,2019年;SchneiderClauß ,2020年)。此外,企業可能難以維持一支健康且受過教育的員工隊伍,同時培養培養有效員工和負責任的公民所需的技能和知識,共同為社會福祉做出貢獻。鑑於這些挑戰,建立策略聯盟對於合作夥伴之間分擔風險、匯集資源、共享知識和促進永續發展目標所必需的創新至關重要,尤其是de Bakker等人所倡導的協作方法所獲得的牽引力。 (2019)等人。 (2021),馬丁內斯等人。 (2019),Vlaisavljevic等人。 (2016)Vurro等人。 (2023)。
儘管人們對永續發展目標做出了廣泛的承諾,越來越多的關於企業對這些目標的貢獻的研究證明了這一點(例如,Al Lawati和Hussainey ,2022 年;Bradley等人,2021 年; de Ruyter等人,2022 年;Emma和Jennifer,2021 年);Gillani等人,2022 ),實際進展仍然有限。約 72% 的公司公開宣稱致力於實現永續發展目標,但只有1% 的公司在實現這些目標方面取得了實質進展(普華永道,2019 年),其中許多公司進展緩慢(Yahya等人,2021 年)。事實上,許多公司優先考慮短期財務利益,這與長期永續發展目標相衝突。這種短期關注往往會導致資源從永續發展投資中轉移,企業更傾向於眼前收益而不是長期永續發展獎勵(《金融時報》,2024年;Kim等人,2019年;Schneider和Clauß ,2020年)。此外,企業可能難以維持一支健康且受過教育的員工隊伍,同時培養培養有效員工和負責任的公民所需的技能和知識,共同為社會福祉做出貢獻。鑑於這些挑戰,建立策略聯盟對於合作夥伴之間分擔風險、匯集資源、共享知識和促進永續發展目標所必需的創新至關重要,尤其是de Bakker等人所倡導的協作方法所獲得的牽引力。(2019),江等人。(2021),馬丁內斯等人。(2019),Vlaisavljevic等人。(2016)和Vurro等人。(2023)。

雖然夥伴關係對於解決永續發展等重大挑戰至關重要,但有證據表明,企業之間的成功差異很大,有些企業表現優於其他企業,有些甚至在參與策略聯盟時遭遇失敗(Ireland等人,2002 年;Martinez等人,2019 年)希爾克戈爾岑,2010 年)作為一個複雜的系統,策略聯盟有時會因夥伴關係而產生緊張關係,給企業帶來額外的負擔(Vurro等人,2024)。也在英國管理雜誌最近引發了一場關於透過策略聯盟參與永續發展目標有效性的辯論( Foroudi等人,2023;Al- Tabbaa等人,2023 )。原因之一可能在於企業擁有的聯盟管理能力程度( Al- Tabba a et al ., 2023; Anand and Khanna, 2000; Foroudi et al ., 2023; Schilk and Goerzen , 2010)。聯盟管理能力被定義為企業獲取、共享、儲存和部署與聯盟管理相關的知識、經驗和學習能力和慣例( Bouncken,2022;KaleSingh,2007)。聯盟管理能力與聯盟策略不同聯盟管理能力更著重於透過協調資源(例如學習、累積和利用聯盟管理知識從策略聯盟中獲得最佳優勢Bouncken et al ., 2022)凱爾辛格,2007 )。透過協作和夥伴關係來實現永續發展通常涉及調動資源來實現環境和社會目標(d e Bakker等人,2019;Vurro等人,2023)。因此,聯盟管理能力可以幫助企業 建立有利於合作和夥伴關係的慣例,確保實現永續發展目標的有效性儘管在許多概念研究中廣泛認識到聯盟管理能力帶來的好處(Bouncken等人,2022 年;SchilkeGoerzen ,2010 年;Vurro等人,2023 年),但缺乏對聯盟管理能力驅動的實證研究。的影響,特別是它們對企業追求永續發展目標的影響。透過探討聯盟管理能力如何影響商業模式創新和永續發展目標績效,本研究提供了更細緻的理解,可以幫助企業更有效地制定策略因此,本研究將探討以下問題聯盟管理能力如何影響與SDG 8和SDG 12相關的績效?
雖然夥伴關係對於解決永續發展等重大挑戰至關重要,但有證據表明,企業之間的成功差異很大,有些企業表現優於其他企業,有些甚至在參與策略聯盟時遭遇失敗(Ireland等人,2002 年;Martinez等人,2019 年)希爾克戈爾岑,2010 年)作為一個複雜的系統,策略聯盟有時會因夥伴關係而產生緊張關係,給企業帶來額外的負擔(Vurro等人,2024)。這也在英國管理雜誌最近引發了一場關於透過策略聯盟參與永續發展目標有效性的辯論( Foroudi等人,2023;Al- Tabbaa等人,2023 )。原因之一可能在於企業擁有的聯盟管理能力程度( Al- Tabba a et al ., 2023;Anand 和 Khanna,2000 年;Foroudi 等人,2023 年;Schilk 和 Goerzen , 2010)。聯盟管理能力被定義為企業獲取、共享、儲存和部署與聯盟管理相關的知識、經驗和學習的能力和慣例( Bouncken等,2022;Kale和Singh,2007)。聯盟管理能力與聯盟策略不同,聯盟管理能力更著重於透過協調資源(例如學習、累積和利用聯盟管理知識)從策略聯盟中獲得最佳優勢(Bouncken et al ., 2022)凱爾和辛格,2007 )。透過協作和夥伴關係來實現永續發展通常涉及調動資源來實現環境和社會目標(d e Bakker等人,2019;Vurro等人,2023)。因此,聯盟管理能力可以幫助企業建立有利於合作和夥伴關係的慣例,確保實現永續發展目標的有效性儘管在許多概念研究中廣泛認識到聯盟管理能力帶來的好處(Bouncken等人,2022 年;SchilkeGoerzen ,2010 年;Vurro等人,2023 年),但缺乏對聯盟管理能力驅動的實證研究。的影響,特別是它們對企業追求永續發展目標的影響。透過探討聯盟管理能力如何影響商業模式創新和永續發展目標績效,本研究提供了更細緻的理解,可以幫助企業更有效地制定策略因此,本研究將探討以下問題聯盟管理能力如何影響與SDG 8和SDG 12相關的績效?

同時,商業模式創新和策略彈性至關重要,在檢視聯盟管理能力與永續發展目標之間的關係時不應忽視Barrales -Molina et al ., 2013; Foroudi et al. , 2023; Herhausen et al ., 2021 ;蘭格等人,2015 帕策爾特人,2008 Spieth 和Schuchert (2018)討論了聯盟內部的挑戰,例如動態、關係和架構問題,這些問題需要整合到業務模型設計中,然後開發一個流程模型,讓企業協作建立新的業務模型(Spieth等人, 2021)。此外,Bouncken和 Fredrich(2016)指出,公司聯盟投資組合的結構可以顯著提高從這些關係中獲得的價值。同樣,Velu (2015)發現第三方聯盟特別能促進商業模式創新,尤其是在年輕的公司。事實上讓策略夥伴參與新的價值創造活動系統可以帶來多種好處,包括增強創新和獲取多樣化資源(Al- Tabba等人,2023 年;Bouncken等人,2023 年;SchneiderClauß , 2020 年)。這揭示了培養企業內部聯盟管理能力的重要性,使聯盟能夠更有效地控制創新成本,獲得更廣泛的資源(例如知識和技術,並分散與經濟價值不確定的創新活動相關的風險等人,2020)。 因此,聯盟管理能力對於旨在保持商業模式創新以應對動態環境需求的公司至關重要(Arndt,2019 ;Arndt,2022 這些能力可以激勵企業重新設計產品和服務,以更好地滿足客戶需求,同時有效地參與永續發展目標(Von Delft 等,2019)。
同時,商業模式創新和策略彈性至關重要,在檢視聯盟管理能力與永續發展目標之間的關係時不應忽視(Barrales -Molina et al ., 2013;Foroudi 等人,2023 年;Herhausen et al ., 2021 ;蘭格等人,2015 ;帕策爾特等人,2008 )。Spieth 和Schuchert (2018)討論了聯盟內部的挑戰,例如動態、關係和架構問題,這些問題需要整合到業務模型設計中,然後開發一個流程模型,讓企業協作建立新的業務模型(Spieth等人, 2021)。此外,Bouncken和 Fredrich(2016)指出,公司聯盟投資組合的結構可以顯著提高從這些關係中獲得的價值。同樣,Velu (2015)發現第三方聯盟特別能促進商業模式創新,尤其是在年輕的公司。事實上,讓策略夥伴參與新的價值創造活動系統可以帶來多種好處,包括增強創新和獲取多樣化資源(Al- Tabba等人,2023 年;Bouncken等人,2023 年;Schneider和Clauß , 2020 年)。這揭示了培養企業內部聯盟管理能力的重要性,使聯盟能夠更有效地控制創新成本,獲得更廣泛的資源(例如知識和技術),並分散與經濟價值不確定的創新活動相關的風險。等人,2020)。因此,聯盟管理能力對於旨在保持商業模式創新以應對動態環境需求的公司至關重要(Arndt,2019 ;Arndt,2022 這些能力可以激勵企業重新設計產品和服務,以更好地滿足客戶需求,同時有效地參與永續發展目標(Von Delft 等,2019)。

此外,策略彈性是組織透過主動或被動地快速回應市場挑戰和機會來應對經濟和政治風險的能力(GrewalTansuhaj ,2001 Herhausen,2021 )。策略靈活性有望使組織能夠快速適應不斷變化的市場條件並利用新出現的機會,從而放大聯盟管理能力對商業模式創新的影響策略靈活的企業能夠迅速應對經濟和政治風險(GrewalTansuhaj ,2001 Herhausen,2021 ),可以更有效地利用其合作夥伴關係。這包括更好地發起活動,例如跨聯盟匯集資源、知識和專業知識。這種適應性創造了一個有利於創新的環境,使企業能夠迅速回應市場動態,並積極利用透過其協作網路發現的機會。透過這種方式,策略靈活性使企業能夠不斷完善和重塑其業務模式(Arndt等人,2022),納入來自其聯盟的新想法、技術和實踐,以保持競爭力和可持續發展。因此,具有高度策略靈活性的公司能夠更好地優化其聯盟管理能力,從而實現更具影響力的商業模式創新,進而維持更好的永續發展目標。
此外,策略彈性是組織透過主動或被動地快速回應市場挑戰和機會來應對經濟和政治風險的能力(GrewalTansuhaj ,2001 ;Herhausen,2021 )。策略靈活性有望使組織能夠快速適應不斷變化的市場條件並利用新出現的機會,從而放大聯盟管理能力對商業模式創新的影響策略靈活的企業能夠迅速應對經濟和政治風險(GrewalTansuhaj ,2001 ;Herhausen,2021 ),可以更有效地利用其合作夥伴關係。這包括更好地發起活動,例如跨聯盟匯集資源、知識和專業知識。這種適應性創造了一個有利於創新的環境,使企業能夠迅速回應市場動態,並積極利用透過其協作網路發現的機會。透過這種方式,策略靈活性使企業能夠不斷完善和重塑其業務模式(Arndt等人,2022),納入來自其聯盟的新想法、技術和實踐,以保持競爭力和可持續發展。因此,具有高度策略靈活性的公司能夠更好地優化其聯盟管理能力,從而實現更具影響力的商業模式創新,進而維持更好的永續發展目標。

借鏡關係觀點強調透過利用組織間資源、知識分享、能力互補和有效治理的策略聯盟來獲得競爭優勢DyerSingh ,1998;Dyer,2018),我們假設聯盟管理能力與永續發展目標績效正相關,商業模式創新和策略靈活性分別在這種關係中起中介作用和調節作用。我們使用結構化調查和多階段資料收集流程,透過 SEM對台灣大型企業樣本測試了概念模型,其中包括代表314 家製造企業的1,125 名高級管理人員和代表247 家服務公司的800 名高級管理人員的回饋.我們的研究結果表明,(1) 聯盟管理能力對永續發展目標(SDG 8 和 12)績效有正面影響,(2) 商業模式創新是聯盟管理能力和永續發展目標( SDG 8 和 12 )績效之間的重要中介因素,( 3)策略彈性正向調節聯盟管理能力與商業模式創新之間以及商業模式創新與SDG績效之間的關係,(4)企業策略彈性透過商業模式調節聯盟管理能力對SDG績效的正面影響創新。
借鏡關係觀點強調透過利用組織間資源、知識分享、能力互補和有效治理的策略聯盟來獲得競爭優勢DyerSingh ,1998;Dyer,2018),我們假設聯盟管理能力與永續發展目標績效正相關,商業模式創新和策略靈活性分別在這種關係中起中介作用和調節作用。我們使用結構化調查和多階段資料收集流程,透過 SEM對台灣大型企業樣本測試了概念模型,其中包括代表314 家製造企業的1,125 名高級管理人員和代表247 家服務公司的800 名高級管理人員的回饋.我們的研究結果表明,(1) 聯盟管理能力對永續發展目標(SDG 8 和 12)績效有正面影響,(2) 商業模式創新是聯盟管理能力和永續發展目標( SDG 8 和 12 )績效之間的重要仲介因素,(3)策略彈性正向調節聯盟管理能力與商業模式創新之間以及商業模式創新與SDG績效之間的關係,(4)企業策略彈性透過商業模式調節聯盟管理能力對SDG績效的正面影響創新。

我們的研究做出了四項重大貢獻。首先,本研究擴展了關係觀理論,論證了聯盟管理能力的重要性以及聯盟管理能力如何與聯盟合作有效催化資源(從聯盟獲得)效率,從而實現永續發展目標。我們的研究與 Martinez 等人的研究一致。 (2019)關於內部能力對永續發展轉型的影響。同時,我們發現商業模式創新是聯盟管理能力和永續發展目標績效之間的關鍵中介因素,而策略靈活性則起到調節作用,增強這些聯盟對商業模式創新的影響,並最終提高永續發展目標績效。這是響應蔣等人的號召。 (2021)對組織策略與永續成果之間的互動進行了更細緻的研究,同時也增進了我們對企業如何利用組織間資源實現永續成長的理解。我們的發現強調了策略靈活性和商業模式創新之間在幫助組織實現永續發展目標方面的動態互動Arndt2022 特別是永續發展目標 8 和 12。租金如何透過以下方式產生的見解:策略夥伴關係,為旨在聯盟以實現可持續成長的優化。其次,我們的研究強調了商業模式創新在促進永續發展轉型中的關鍵作用,展示了策略調整如何將聯盟利益融入永續發展策略,支持永續發展目標 8 和 12(Pedersen,2018;SchneiderClauß ,2020;Spieth等).,2019)。我們的研究結果表明,商業模式創新是一個針對外部性而不斷發展的動態框架,對於維持企業內部的就業品質和資源效率至關重要(Arndt等人,2022 年;BounckenFredrich,2016a;Spieth等人,2021 年)維盧2015 年)。
我們的研究做出了四項重大貢獻。首先,本研究擴展了關係觀理論,論證了聯盟管理能力的重要性以及聯盟管理能力如何與聯盟合作有效催化資源(從聯盟獲得)效率,從而實現永續發展目標。我們的研究與 Martinez 等人的研究一致。(2019)關於內部能力對永續發展轉型的影響。同時,我們發現商業模式創新是聯盟管理能力和永續發展目標績效之間的關鍵中介因素,而策略靈活性則起到調節作用,增強這些聯盟對商業模式創新的影響,並最終提高永續發展目標績效。這是響應蔣等人的號召。(2021)對組織策略與永續成果之間的互動進行了更細緻的研究,同時也增進了我們對企業如何利用組織間資源實現永續成長的理解。我們的發現強調了策略靈活性和商業模式創新之間在幫助組織實現永續發展目標方面的動態互動(Arndt等,2022 ),特別是永續發展目標 8 和 12。租金如何透過以下方式產生的見解:策略夥伴關係,為旨在聯盟以實現可持續成長的優化。其次,我們的研究強調了商業模式創新在促進永續發展轉型中的關鍵作用,展示了策略調整如何將聯盟利益融入永續發展策略,支持永續發展目標 8 和 12(Pedersen等,2018;Schneider和Clauß ,2020;Spieth等).,2019)。我們的研究結果表明,商業模式創新是一個針對外部性而不斷發展的動態框架,這對於維持企業內部的就業品質和資源效率至關重要(Arndt等人,2022 年;Bouncken和Fredrich,2016a;Spieth等人,2021 年)維盧,2015 年)。

此外,我們確立了內部能力在有效管理外部合作夥伴關係以實現商業模式創新的重要性(Clauss et al ., 2021; Hock- Doepgen et al ., 2020; Mezger , 2014; Teece, 2018)。這強調需要強而有力的內部管理實踐以及外部合作來實現永續的成果。最後,我們強調策略彈性在聯盟管理能力、商業模式創新和永續發展目標績效之間的調節作用,提高關係租金和永續發展目標成果(Dyer 和 Singh,1998 年;Dyer、Singh 和Hesterly 2018 )。策略靈活性既可以增強能力,也可以增強復原力機制,對於實現永續發展目標的複雜路徑至關重要。這為策略靈活性在永續發展目標績效中的作用增加了一個新的維度,並倡導在能力發展和聯盟管理方面採取綜合方法。
此外,我們確立了內部能力在有效管理外部合作夥伴關係以實現商業模式創新的重要性(Clauss et al ., 2021;Hock- Doepgen 等人,2020 年; Mezger , 2014;Teece, 2018)。這強調需要強而有力的內部管理實踐以及外部合作來實現永續的成果。最後,我們強調策略彈性在聯盟管理能力、商業模式創新和永續發展目標績效之間的調節作用,提高關係租金和永續發展目標成果(Dyer 和 Singh,1998 年;Dyer、Singh 和 Hesterly 2018 )。策略靈活性既可以增強能力,也可以增強復原力機制,對於實現永續發展目標的複雜路徑至關重要。這為策略靈活性在永續發展目標績效中的作用增加了一個新的維度,並倡導在能力發展和聯盟管理方面採取綜合方法。

2.理論基礎與假設發展
2. 理論基礎和假設發展

2.1 .關係觀理論聯盟管理能力與SDG績效

建立在基於資源的觀點(RBV)(Barney,1991)的基礎上,關係觀點認為競爭優勢可能來自透過其關係網絡存取的資源(Dyer&Singh,1998)。聯盟透過匯集不同的能力並促進獲取互補的外部資源、新知識和想法來提供顯著的策略利益(Buckley,2009;Park,2004)。這些合作使企業能夠創造獨特的投資並促進共享的學習過程,這對於產生關係租金至關重要——聯盟特有的競爭優勢,同時也是競爭對手難以複製的(DyerSingh,1998)。這種整合不僅提高了效率,也拓寬了策略範圍,使企業能夠實現自身無法實現的目標。關係觀點認為,聯盟管理能力在維持這些夥伴關係的有效性方面發揮著至關重要的作用(SchilkeGoerzen ,2010)。聯盟管理能力包括共享、獲取和部署透過聯盟獲得的資源,以最大化合作夥伴利益Vurro等人,2024)。此外,它們使企業能夠在交換關係中共同創造競爭優勢(Vurro等人,2023)。
建立在基於資源的觀點(RBV)(Barney,1991)的基礎上,關係觀點認為競爭優勢可能來自透過其關係網絡存取的資源(Dyer&Singh,1998)。聯盟透過匯集不同的能力並促進獲取互補的外部資源、新知識和想法來提供顯著的策略利益(Buckley,2009;Park,2004)。這些合作使企業能夠創造獨特的投資並促進共享的學習過程,這對於產生關係租金至關重要——聯盟特有的競爭優勢,同時也是競爭對手難以複製的(DyerSingh,1998)。這種整合不僅提高了效率,也拓寬了策略範圍,使企業能夠實現自身無法實現的目標。關係觀點認為,聯盟管理能力在維持這些夥伴關係的有效性方面發揮著至關重要的作用(SchilkeGoerzen ,2010)。聯盟管理能力包括共享、獲取和部署透過聯盟獲得的資源,以最大化合作夥伴利益Vurro等人,2024)。此外,它們使企業能夠在交換關係中共同創造競爭優勢(Vurro等人,2023)。

聯盟管理能力對於企業追求永續發展目標至關重要,特別是分別維持經濟成長、優質就業(永續發展目標 8)資源效率永續發展目標 12) 。這些能力包括組織間協調、主動性、轉型和學習,每項能力都有助於實現永續發展目標(DyerSingh,1998;LaneLubatkin ,1998)。組織間協調包括確定任務要求、了解合作夥伴的相互依賴性以及指定執行程序(Schreiner,2009)。協調透過確保所有合作夥伴統一實施勞動力計劃來維持工作品質和就業率。例如,在兩家科技公司之間的策略聯盟中,有效的協調可確保雙方統一實施商定的勞動力計劃,例如技能提升研討會和創新驅動。這種一致性支持公平且令人滿意的工作環境,有利於公司的可持續經濟績效Erten等人,2022 年)。此外,協調一致的努力有助於維持資源效率並減少夥伴關係中的浪費。透過密切合作,企業可以整合創新技術並調整營運策略,以盡量減少對環境的影響,開發可持續的供應鏈,優化資源利用(Bolton等人,2021)。永續發展措施的成功往往取決於良好協調的執行。當組織間協調有力時,如果統一採用,有效實施整合產品和跨聯盟合作夥伴共享知識可以帶來顯著的永續發展進步(Kamalaldin等人,2020)。另一方面,如果協調程度低,工作可能會脫節,無法達到預期目標(Bolton et al ., 2021)。此外,在缺乏權威治理機制的環境中,跨組織邊界的協調至關重要。有效的協調有助於防止誤解、減少衝突、遏制機會主義行為、維持聯盟內部的信任與合作(ClaussBouncken ,2019;HoetkerMellewigt) ,2009;SchilkeGoerzen ,2010)。
聯盟管理能力對於企業追求永續發展目標至關重要,特別是分別維持經濟成長、優質就業(永續發展目標 8)資源效率永續發展目標 12) 。這些能力包括組織間協調、主動性、轉型和學習,每項能力都有助於實現永續發展目標(Dyer和Singh,1998;Lane和Lubatkin ,1998)。組織間協調包括確定任務要求、了解合作夥伴的相互依賴性以及指定執行程序(Schreiner等,2009)。此協調透過確保所有合作夥伴統一實施勞動力計劃來維持工作品質和就業率。例如,在兩家科技公司之間的策略聯盟中,有效的協調可確保雙方統一實施商定的勞動力計劃,例如技能提升研討會和推動大陸統。這種一致性支持公平且令人滿意的工作環境,有利於公司的可持續經濟績效(Erten等人,2022 年)。此外,協調一致的努力有助於維持資源效率並減少夥伴關係中的浪費。透過密切合作,企業可以整合創新技術並調整營運策略,以盡量減少對環境的影響,開發可持續的供應鏈,優化資源利用(Bolton等人,2021)。永續發展措施的成功往往取決於良好協調的執行。當組織間協調有力時,如果統一採用,有效實施整合產品和跨聯盟合作夥伴共享知識可以帶來顯著的永續發展進步(Kamalaldin等人,2020)。另一方面,如果協調程度低,工作可能會脫節,無法達到預期目標(Bolton et al ., 2021)。此外,在缺乏權威治理機制的環境中,跨組織邊界的協調至關重要。有效的協調有助於防止誤解、減少衝突、遏制機會主義行為、維持聯盟內部的信任與合作(Clauss和Bouncken ,2019;Hoetker和Mellewigt),2009;SchilkeGoerzen ,2010)。

Alliance proactiveness is “a company’s efforts to identify potentially valuable partnering opportunities” (Sarkar et al., 2001: 702). This is grounded in routines that link opportunity recognition (e.g., for sustainable development projects) with the proactive initiation of alliances to address those opportunities (Schilke and Goerzen, 2010). This proactivity is a driver for SDG achievement. This is because environmental proactivity differentiates firms that actively implement practices and initiatives aimed at improving sustainability, thus making a bold impact and those that only react to external requirements and pressures, such as governmental regulations regarding pollution or reporting (González-Benito and González-Benito, 2006). Proactivity in alliances allows firms to implement practices and initiatives that significantly promote sustainable economic growth and work environment and target responsible consumption and production.
聯盟主動性是“公司為尋找潛在有價值的合作機會所做的努力”(Sarkar et al., 2001: 702)。這是基於將機會識別(例如,用於可持續發展專案)與積極發起聯盟以解決這些機會聯繫起來的例行程式(SchilkeGoerzen,2010)。這種積極性實現可持續發展目標的驅動力。這是因為環境主動性將積極實施旨在提高可持續性的實踐和舉措的公司區分開來,從而產生大膽的影響,而那些只對外部要求和壓力做出反應的公司,例如關於污染或報告的政府法規(González-Benito González-Benito,2006 年)。積極主動地加入聯盟使公司能夠實施顯著促進可持續經濟增長和工作環境的實踐和舉措,並以負責任的消費和生產為目標。

Alliance transformation equips firms to adapt governance mechanisms—like revising contracts or altering coordination methods—to effectively respond to emerging challenges (Reuer and Zollo, 2000). This capability is particularly crucial in sustainable development initiatives that aim to transform organisational practices or supply chains, which are susceptible to various shifts and disruptions over time. Successfully adapting alliance structures and processes is essential to mitigate the impacts of changes in the economic, environmental, or regulatory landscape, preventing sustainability projects from derailing (Clauss and Tangpong, 2018; Heide and Miner, 1992). Such flexibility is vital for ensuring that sustainability initiatives are not only initiated but also seen through to completion without delays or premature termination, directly supporting and promoting economic growth, productive employment, and production patterns. By maintaining this adaptive capacity, firms can continuously align their collaborative efforts with evolving sustainability targets, ensuring their initiatives remain effective and relevant in promoting broader environmental and social progress.
聯盟轉型使公司能夠調整治理機制,例如修改合同或更改協調方法,以有效應對新出現的挑戰(Reuer Zollo,2000 年)。這種能力在旨在改變組織實踐或供應鏈的可持續發展計劃中尤為重要,因為隨著時間的推移,這些實踐或供應鏈容易受到各種變化和中斷的影響。成功調整聯盟結構和流程對於減輕經濟、環境或監管環境變化的影響,防止可持續發展項目脫軌至關重要(ClaussTangpong,2018;Heide Miner,1992 年)。這種靈活性對於確保可持續發展計劃不僅啟動而且完成而不延誤或過早終止至關重要,直接支援和促進經濟增長、生產性就業生產模式。通過保持這種適應能力,公司可以不斷將其協作努力與不斷變化的可持續發展目標保持一致,確保其舉措在促進更廣泛的環境和社會進步方面保持有效和相關性。

Lastly, inter-organisational learning is key to maximising the value of collaborations (Dyer and Singh, 1998). As the achievement of SDGs was closely linked to processes, products and services (Herrero et al., 2021; van Der Waal et al., 2021), those firms will be better able to learn from their alliances. Learning facilitates the focal firm to improve its knowledge about market developments, technologies, and procedures (van Kleef and Roome, 2007). If inter-organisational learning is high, more complex, and tacit knowledge can be transferred. This also incorporates co-learning through which both partners utilise complementary competencies to create novel outcomes (Clauss and Kesting, 2017) and innovation (Rothaermel and Deeds, 2006). Due to the benefits brought by alliance management capabilities, we posit:
最後,組織間學習是最大化合作價值的關鍵(Dyer Singh,1998年)。由於可持續發展目標的實現與流程、產品和服務密切相關(Herrero et al., 2021;van Der Waal et al., 2021),這些公司將能夠更好地從他們的聯盟中學習。學習有助於重點公司提高其對市場發展、技術和程序的瞭解(van Kleef Roome,2007 年)。如果組織間學習很高,則可以轉移更複雜和隱性知識。這也包括共同學習,通過共同學習,雙方利用互補的能力來創造新的成果(ClaussKesting,2017 年)和創新(Rothaermel Deeds,2006 年)。由於聯盟管理能力帶來的好處,我們認為:

H1. Firms alliance management capability has a positive effect on their SDG performance.
H1. 公司的聯盟管理能力對其 SDG 績效有積極影響

The mediating role of business model innovation
商業模式創新的仲介作用

Business models outline a firm's approach to creating and delivering value, from engaging customers to generating profits (Zott and Amit, 2010; Casadesus-Masanell and Ricart, 2010; Teece, 2010). Business model innovation is noticed asdesigned, novel, and non-trivial changes to the key elements of a firm’s business model and/or the architecture linking these elements” (Foss and Saebi, 2017: 201). Business model innovation can either be a firm reaction to changing market conditions or a proactive strategic choice to develop the firm ahead of the competition (Clauss et al., 2021). Firms innovate their business models in response to various triggers, such as technological disruptions (Cozzolino et al., 2018), changing market conditions (Karimi and Walter, 2016), severe external crises (Clauss et al., 2022), or commitments to corporate sustainability, which require transformative changes to established business practices.
商業模式概述了公司創造和交付價值的方法,從吸引客戶到產生利潤(Zott Amit,2010 年;Casadesus-Masanell Ricart,2010 年;Teece,2010 年)。商業模式創新被認為是 對公司商業模式的關鍵要素和/或連接這些要素的架構進行設計、新穎和非平凡的改變」(Foss Saebi,2017:201)。商業模式創新可以是對不斷變化的市場條件的堅定反應,也可以是在競爭之前發展公司的積極戰略選擇(Clauss et al., 2021)。公司根據各種觸發因素創新其商業模式,例如技術顛覆(Cozzolino ,2018 年)、不斷變化的市場條件(Karimi Walter,2016 年)、嚴重的外部危機(Clauss等人,2022 年)或對企業可持續發展的承諾,這需要對既定的商業實踐進行變革。

Alliance management capabilities play a crucial role in fostering business model innovation, particularly in contexts focused on sustainability. These capabilities enable firms to harness external resources and knowledge effectively, which are essential for innovating business models that contribute to SDGs. For instance, research indicates that firms with high alliance management capabilities are more successful in integrating and leveraging inter-organisational relationships for new product development and co-innovation, both critical components of business model innovation (Rothaermel and Deeds, 2006; Kauppila, 2015; Zahoor et al., 2023). Empirical studies suggest that proactive management of alliances facilitates the exploration and exploitation of external knowledge, enabling firms to co-develop innovative solutions and radically transform their business models towards sustainability (Inigo et al., 2020; Kauppila, 2015). This is effective when firms engage with partners whose capabilities complement or significantly differ from their own. Such strategic collaborations can provide access to novel ideas and practices that can be integrated into the firm’s business model, promoting agility and adaptiveness in rapidly changing markets (Bocken et al., 2014; Inigo et al., 2017). The ability to manage alliances proactively allows firms to align their innovation efforts with the SDGs effectively. By doing so, they not only meet their sustainability targets but also drive competitive advantage through differentiated business models that capitalize on sustainability-oriented innovation (Hock-Doepgen et al., 2020; Snihur and Wiklund, 2019). Therefore, enhancing alliance management capabilities is not merely about managing relationships but also about strategically utilizing these relationships to rethink and restructure the business models essential for achieving sustainable outcomes.
聯盟管理能力在促進商業模式創新方面發揮著至關重要的作用,尤其是在注重可持續發展的環境中。這些功能使公司能夠有效地利用外部資源和知識,這對於創新有助於實現可持續發展目標的商業模式至關重要。例如,研究表明,具有較高聯盟管理能力的公司更成功地整合和利用組織間關係進行新產品開發和共同創新,這兩者都是商業模式創新的關鍵組成部分(Rothaermel Deeds,2006 年;Kauppila,2015 年;Zahoor等人,2023年)。實證研究表明,聯盟的主動管理有助於探索和利用外部知識,使公司能夠共同開發創新解決方案,並從根本上轉變其商業模式,以實現可持續性(Inigo 人,2020 年;Kauppila,2015 年)。當公司與能力互補或與自身能力明顯不同的合作夥伴合作時,這種做法非常有效。這種戰略合作可以提供獲得新想法和實踐的機會,這些想法和實踐可以整合到公司的商業模式中,在快速變化的市場中促進敏捷性和適應性(Bocken等人,2014年;Inigo et al., 2017)。主動管理聯盟的能力使公司能夠有效地將其創新工作與 SDG 保持一致。通過這樣做,他們不僅實現了可持續發展目標,而且還通過利用以可持續發展為導向的創新的差異化商業模式來推動競爭優勢(Hock-Doepgen 等人。, 2020;SnihurWiklund,2019 年)。因此,增強聯盟管理能力不僅僅是管理關係,還包括戰略性地利用這些關係來重新思考和重組對實現可持續成果至關重要的商業模式。

Business model innovations will have twofold effects on the SDG performance of focal firms. First, in line with previous research (Abdelkafi and Täuscher, 2016; Ludeke-Freund and Dembek, 2017; Pieroni et al., 2019), these transformed business models facilitate that firms can truly change their logic towards sustainability and establish a sustainability logic that drives strategies and resource allocations, in turn providing a much better breeding ground for quality employment and resource efficiency. Second, business model innovation has the potential to further strengthen how knowledge and resources from alliance partners can be transformed into production enhancement. As such, we postulate:
B實用模型創新將對重點公司的SDG績效產生雙重影響。首先,與之前的研究一致(Abdelkafi Täuscher,2016 年;Ludeke-Freund Dembek,2017 年;Pieroni et al., 2019)的研究中發表的文章中,這些轉變的商業模式有助於企業真正改變其對可持續發展的邏輯,並建立驅動戰略資源分配的可持續發展邏輯,從而為優質就業和資源效率提供更好的溫床。其次,商業模式創新有可能進一步加強將聯盟合作夥伴的知識和資源 轉化為生產增強的方式。 因此,我們假設:

H2. Firms business model innovation mediates the positive effect of their alliance management capability on SDG performance.
H2. 公司的商業模式創新仲介了其聯盟管理能力對SDG績效的積極影響。

The moderating role of strategic flexibility
戰略靈活性的調節作用

Strategic flexibility, viewed through the lens of the relational view, captures a firm's ability to adapt, change, and reconfigure itself in response to shifts within its network of alliances and external relationships (Brozovic, 2018; Sanchez, 1995; Teece, 2012). Defined as "the organisational ability to manage economic and political risks by promptly responding in a proactive or reactive manner to market threats and opportunities" (Grewal and Tansuhaj, 2001: 72), strategic flexibility is cultivated through structural and cultural conditions that empower firms to make bold, timely changes when strategically necessary (Bock et al., 2012). Doz and Kosonen (2010) argue that effective strategic management demands sensitivity to external shifts, a top management team's collective commitment to decisive action, and the ability to rapidly reallocate resources to meet new challenges. From the relational view, strategic flexibility strengthens a firm's ability to leverage its alliances effectively. Competitive advantages arise from strategic networks facilitating complementary resources, knowledge-sharing routines, effective governance, and relation-specific assets (Dyer and Singh, 1998). With strategic flexibility, firms can translate external insights from alliances into actionable strategies for business model innovation while achieving sustainable economic growth, quality employment, and resource efficiency. High alliance management capabilities can more effectively translate into business model innovation if the firm proactively undertakes holistic transformation rather than merely reacting to external pressures or regulations. Although alliance management capabilities may not directly shape strategic flexibility, they are optimized when a firm possesses inherent agility. With stagnant progress on SDG 8 and SDG 12 (Lim, 2022) and disruptions caused by the COVID-19 pandemic, the importance of strategic flexibility in relational contexts becomes increasingly clear. This flexibility enables firms to adapt and realign their business models quickly, aligning them with these SDGs. Companies that harness strategic flexibility can use business model innovation as a catalyst for improved SDG performance by effectively tapping into alliances and external networks. Thus, strategic flexibility plays a crucial moderating role in ensuring that alliance management capabilities lead to successful business model innovation. Given the above, we propose:
從關係視角的角度來看,戰略靈活性捕捉了公司適應、改變和重新配置自身以應對其聯盟網路和外部關係內部變化的能力(Brozovic,2018;Sanchez,1995 年;Teece,2012 年)。戰略靈活性被定義為「通過積極主動或被動地迅速應對市場威脅和機遇來管理經濟和政治風險的組織能力」(Grewal Tansuhaj,2001:72),戰略靈活性是通過結構和文化條件培養的,這些條件使公司能夠在戰略必要時做出大膽、及時的改變(Bock et al., 2012)。 DozKosonen (2010) 認為,有效的戰略管理需要對外部變化的敏感性、高層管理團隊對果斷行動的集體承諾以及快速重新分配資源以應對新挑戰的能力。從關係的角度來看,戰略靈活性增強了公司有效利用其聯盟的能力。競爭優勢來自促進互補資源、知識共用例程、有效治理和特定關係資產的戰略網路(Dyer Singh,1998)。憑藉戰略靈活性,公司可以將來自聯盟的外部見解轉化為可行的商業模式創新戰略,同時實現可持續的經濟增長、高品質的就業和資源效率。如果公司積極進行整體轉型,而不僅僅是對外部壓力或法規做出反應,那麼高度的聯盟管理能力可以更有效地轉化為商業模式創新。 儘管聯盟管理能力可能不會直接影響戰略靈活性,但當公司擁有內在的敏捷性時,它們就會得到優化。隨著 SDG 8 和 SDG 12 的進展停滯不前(Lim,2022 年)以及 COVID-19 大流行造成的中斷,戰略靈活性在關係環境中的重要性變得越來越明顯。這種靈活性使公司能夠快速適應和重新調整其業務模式,使其與這些可持續發展目標保持一致。利用戰略靈活性的公司可以通過有效利用聯盟和外部網路,將業務模式創新作為提高可持續發展目標績效的催化劑。因此,戰略靈活性在確保聯盟管理能力導致成功的商業模式創新方面發揮著至關重要的調節作用。鑒於上述情況我們建議

H3. Firms strategic flexibility moderates the positive effect of alliance management capability on business model innovation.
H3.企業的戰略靈活性調節了聯盟管理能力對商業模式創新的積極影響。

H4. Firms strategic flexibility moderates the positive effect of business model innovation on SDG performance.
H4.企業的戰略靈活性調節了商業模式創新SDG績效的積極影響。

H5. Firms strategic flexibility moderates the indirect effect of alliance management capability via business model innovation on SDG performance.
H5.企業的戰略靈活性調節了通過商業模式創新實現的聯盟管理能力對SDG績效的間接影響

Our conceptual model is visualized in Figure 1.
我們的概念模型如圖 1 所示。

[Insert Figure 1 here]
[在此處插入圖 1]

4. Method
4.方法

4.1. Sample
4.1. 樣本

Method
方法

Sample
樣本

The conceptual model of this study was tested on a sample of large firms, with 500 firms from the manufacturing sector (89%) and 500 firms from the service sector (11%) in Taiwan. The firms were randomly selected from the Ministry of Economic Affairs of Taiwan and were in operation for at least five years (Ministry of Economic Affairs, 2022). The similarities between manufacturing and service industries are: (1) they are enthusiastic to engage in SDG 8 and SDG 12, which emphasise social and eco-innovation, directly influence businesses (UN, 2015). SDG 8 aims to promote sustainable economic growth while ensuring access to quality employment opportunities (Rai et al., 2019). SDG 12 focuses on improving resource efficiency to build environmentally friendly workplaces (Filho et al., 2022). (2) both manusfacturing and service sectors are eager to collaborat with their overseas alliances to reduce production carbon and environmental issues as well as health and safety issues including total employement as such (Ministry of Economic Affairs, 2023).
本研究的概念模型在大公司樣本上進行了測試,其中 500 家公司來自製造業 (89%) 和 500 家來自服務業的公司 (11%)。這些公司是從台灣經濟部隨機選擇的,運營至少五年(Ministry of Economic Affairs,2022)。製造業和服務業之間的相似之處是:(1) 他們熱衷於參與強調社會和生態創新的 SDG 8 和 SDG 12,直接影響企業(UN,2015)。可持續發展目標 8 旨在促進可持續經濟增長,同時確保獲得優質就業機會(Rai et al.,2019)。SDG 12 側重於提高資源效率以建立環境友好型工作場所(Filho et al., 2022)。(2) 製造業和服務業都渴望與海外聯盟合作,以減少生產碳和環境問題,以及健康和安全問題,包括總就業人數(經濟事務部,2023)。

The selection of large firms in Taiwan was due to the fact that such large firms have resources to set up more than two alliances overseas and had the publicly SDG performance as required by the purpose of this study. A challenging part in this study was to explore the relationship among the alliances and determines whether and how alliances engage in senior managers’ management capability to achieve SDG performance by improving business model innovation under the impact of strategic flexibility. The selection of these industries was made based on their relevance to the variables in the study and also considering Taiwan’s dynamic, export-driven economy dominated by large firms. This sample was chosen to be representative of an East Asian economy where entrepreneurship and SDG practices are emphasized by government legislation, and large firms have more resources to engage in such practices (Ministry of Economic Affairs, 2022). Moreover, these large firms account for a significant proportion ( 57.8 percent) of total overseas investment (Ministry of Economic Affairs, 2022). The senior managers of these firms were targeted for data collection as they were expected to have the necessary knowledge and expertise related to firm alliance management capability, business model innovation, and performance. For example, the selection of senior managers were based on their professional knowledge in the issues such as employee health and safety, increasing total employment, increasing qualified employment, maintaining existing employment, and compliance with health and safety regulations, reducing environmental impact, lower energy consumed per unit, lower materials employed per unit, higher production or service provision flexibility, and higher production or service provision capacity, and the impact of business model innovation. The proposed relationships were tested through a two-phase data collection process.
選擇臺灣的大公司是因為這些大公司有資源在海外建立兩個以上的聯盟,並且按照本研究的目的要求公開了 SDG 的表現 本研究的一個具有挑戰性的部分是探索聯盟之間的關係並確定聯盟是否以及如何參與高級管理人員的管理能力,通過在戰略靈活性的影響下通過改善商業模式創新來實現可持續發展目標。這些行業的選擇是基於它們與研究中變數的相關性,並考慮了臺灣由大公司主導的充滿活力的出口驅動型經濟。該樣本被選為東亞經濟體的代表,該國政府立法強調創業精神和可持續發展目標的實踐,大公司有更多的資源來從事此類實踐(經濟事務部,2022 年)。此外,這些大公司佔海外投資總額的很大一部分 (57.8%)(經濟部,2022 年)。 這些公司的高級管理人員成為數據收集的目標,因為他們被期望具備與公司聯盟管理能力、商業模式創新和績效相關的必要知識和專業技能。 例如,高級管理人員的選擇是基於他們在員工健康和安全、增加總就業、增加合格就業、維持現有就業以及遵守健康和安全法規等問題上的專業知識降低環境影響、降低單位能耗、降低單位使用的材料、提高生產或服務提供靈活性、提高生產或服務提供能力,以及商業模式創新的影響。 提議的關係通過兩階段數據收集過程進行了測試。

To address potential bias in the survey process, we adopted a multi-respondent approach to collect data from the headquarters (HQ) of the selected firms in Taiwan. This approach provides opportunities for corroboration and therefore, alleviates potential common method bias that arises from the single respondent design discussed in prior research that resorts to self-reported data from senior managers (Chang et al., 2024; Simsek, Lubatkin, Veiga, and Dino, 2009; Simsek, Veiga, and Lubatkin, 2007). Our multi-respondent design offers greater internal validity than the single respondent design adopted in prior research (e.g., Al-Tabbaa et al., 2023; Al-Tabbaa and Zahoor, 2023, 2024; Leischnig et al., 2014).
為了解決調查過程中的潛在偏見,我們採用了多受訪者方法,從選定的臺灣公司的總部 (HQ) 收集數據。這種方法提供了證實的機會,因此減輕了先前研究中討論的單一受訪者設計所產生的潛在通用方法偏差,該設計訴諸高級管理人員的自我報告數據(Chang 等人,2024 年;Simsek、Lubatkin、Veiga 和 Dino,2009 年;Simsek、Veiga 和 Lubatkin,2007 年)。我們的多受訪者設計提供了比先前研究中採用的單受訪者設計更高的內部效度(例如,Al-Tabbaa等人,2023 年;Al-Tabbaa 和 Zahoor,2023 年、2024 年;Leischnig et al., 2014)。

In addition, the survey instrument was developed in English and then translated into Chinese by a native speaker, followed by back-translation to ensure accuracy (Usunier, 1998). The surveys were sent through postal delivery with pre-coded identification numbers and a cover letter explaining the research purpose and materials of research ethics. As an incentive, each firm was provided with a reciprocal report. Confidentiality of responses was assured, and no individual responses were accessible to anyone within the firm. To further encourage response rates, this study received support from the university’s alumni association. Following established procedures to enhance response rates (Podsakoff et al., 2003), the key informants received a full questionnaire survey pack, along with a first and second reminder comprising of a full questionnaire pack and telephone contact.
此外,調查工具是用英文開發的,然後由母語人士翻譯成中文,然後進行回譯以確保準確性(Usunier, 1998)。調查通過郵寄方式發送,並附有預先編碼的身份證號碼和一封解釋研究目的和研究倫理材料的求職信。作為激勵措施,每家公司都收到了一份互惠報告。確保回復的機密性,公司內部的任何人都無法訪問個人回復。為了進一步提高回復率,這項研究得到了該大學校友會的支援。遵循提高回復率的既定程式(Podsakoff et al., 2003),關鍵資訊提供者收到了一份完整的問卷調查包,以及由完整的問卷包和電話聯繫組成的第一次和第二次提醒。

Common method bias
Common 方法偏差

To mitigate ex-ante common method bias (CMB), several procedures were implemented following the recommendations of Podsakoff et al. (2003). First, the measurement items were randomly organized within the survey to avoid order effects. Second, all items were neutrally worded to reduce the chances that respondents would guess the underlying theory while filling out the survey. Third, the length of the questionnaire was minimized to prevent respondent fatigue. Fourth, clear instructions for completing the survey instrument were provided to enhance response accuracy. Fifth, we collected data at three different time points (each time interval is 2 months). Finally, to reduce the influence of social desirability ( bias, confidentiality and anonymity were ensured for all respondents.
為了減輕事前通用方法偏差 (CMB),按照 Podsakoff 等人 (2003) 的建議實施了幾個程式。首先,在調查中隨機組織測量專案以避免順序效應。其次,所有專案都採用中立的措辭,以減少受訪者在填寫調查時猜測基本理論的機會。第三,問卷的長度被最小化,以防止受訪者疲勞。第四,為完成調查工具提供了明確的說明,以提高回答的準確性。第五,我們在三個不同的時間點收集數據 (每個時間間隔為2個月)。最後,為了減少社會期望的影響確保所有受訪者的偏見、保密性和匿名性。

The survey questionnaire was administered to multiple senior managers from each firm’s headquarter across 1,000 headquarters in Taiwan. After excluding 126 incomplete responses, a total of 1,114 responses were obtained from 311 manufacturing firms and 793 responses from 245 service firms. The number of respondents ranged from 2 to 4. Among the respondent firms, 26.4% had been operational for over 15 years, and 72.3% employed a minimum of 500 employees. The average age of the firms was 9.58 years, and the average number of employees was 663.67. To assess non-response bias, we compared early (first 10%) and late (last 10%) respondents and found no significant differences in terms of firm age (t = 0.82 p = 0.41) or firm size (t = 1.04, p = 0.30) (Armstrong and Overton, 1977).
調查問卷對來自臺灣 1,000 家總部的每家公司總部的多名高級管理人員進行了調查。在排除 126 份不完整的回復后,總共收到了來自 311 家製造公司的 1,114 份回復和來自 245 家服務公司的 793 份回復。受訪者人數從 2 到 4 人不等。在受訪公司中,26.4% 已運營超過15年,72.3%僱用至少500名員工。公司的平均年齡為9.58歲,平均員工人數為663.67人。為了評估無反應偏倚,我們比較了早期(前 10%)和晚期(最後 10%)受訪者,發現公司年齡 (t = 0.82 p = 0.41) 或公司規模 (t = 1.04,p = 0.30) 沒有顯著差異 (Armstrong Overton,1977)。

Measures
措施

The measurement items in this study were derived from prior research, and their wording and anchoring can be found in the Appendix. All items used a five-point Likert scale with endpoints of 1 (strongly disagree) and 5 (strongly agree). To ensure the validity of the measurement items, a board comprised of five scholars and five managers was convened to pre-test the questionnaire, resulting in high face validity (0.90) and content validity (0.92).
本研究中的測量項目來自先前的研究,它們的措辭和錨定可以在附錄中找到。所有專案都使用五點李克特量表,終點為1(非常不同意)和5(非常同意)。為了確保測量專案的有效性,召集了一個由5名學者和5名管理人員組成的委員會對問卷進行預測試,結果產生了高表面效度 (0.90) 和內容效度 (0.92)。

The items used to assess alliance management capability were adapted and modified from Schilke and Goerzen (2010). A total of 18 items were used to measure firm alliance management capability (Appendix, α = 0.98, F (555, 1351) = 2.26, p < 0.001).
用於評估聯盟管理能力的專案改編和修改自 Schilke 和 Goerzen (2010)。共有18個專案用於衡量公司聯盟管理能力 (附錄,α = 0.98,F(555, 1351) = 2.26,p < 0.001)。

The items used to evaluate strategic flexibility were adapted from Grewal and Tansuhaj (2001). This measure captures the nature of the firm possessing liquid resources or options to enhance the speed and extent of its manoeuvring capabilities. A total of 5 items were used to measure strategic flexibility (Appendix, α = 0.74, F (555, 1351) = 1.97, p < 0.001).
用於評估戰略靈活性的專案改編自 Grewal 和 Tansuhaj (2001)。該指標捕捉了公司擁有流動資源或選擇以提高其操縱能力的速度和程度的公司的性質。共有 5 個項目用於衡量戰略靈活性(附錄,α = 0.74,F(555, 1351) = 1.97,p < 0.001)。

The items used to measure business model innovation were adapted from Von Delft et al. (2019). This measure captures the firm’s overall ability to create and capture value by including four interlocking elements: customer value proposition, key resources, key processes, and profit formula. A total of five items were used to measure business model innovation (Appendix, α = 0.77, F (555, 1351) = 1.61, p < 0.001).
用於衡量商業模式創新的項目改編自 Von Delft et al. (2019)。該指標通過包括四個環環相扣的要素來捕捉公司創造和獲取價值的整體能力:客戶價值主張、關鍵資源、關鍵流程和利潤公式。共有五個專案用於衡量商業模式創新(附錄,α = 0.77,F(555, 1351) = 1.61,p < 0.001)。

The SDG performance data for this study were retrieved from the Taiwan Economic Journal’s (TEJ) publicly available database. TEJ is a leading credit analysis research agency in Taiwan, similar to Standard & Poor’s, Moody’s, and Fitch Group in the United States. It is a comprehensive financial services provider in Taiwan and is extensively used in scholarly research to examine the performance of Taiwan-listed companies. Studies have also shown that TEJ is a reliable source of financial information for Taiwan-listed firms (Chu, 2004; Hsu et al., 2013; Hwang et al., 2012).
本研究的 SDG 績效數據取自台灣經濟雜誌 (TEJ) 的公開資料庫。TEJ是台灣領先的信用分析研究機構,類似於美國的標準普爾、穆迪和惠譽集團。它是台灣的綜合性金融服務提供者,廣泛用於學術研究,以考察臺灣上市公司的表現。研究還表明,TEJ 是臺灣上市公司的可靠財務資訊來源(Chu,2004 年;Hsu et al., 2013;Hwang et al., 2012)。

In line with PITEC (e.g., Sáez-Martínez et al., 2016) or CIS (e.g., Ghisetti et al., 2015) to measure SDG 8 targets (Decent Work and Economic Growth) in our proxy of social innovation and items connected to SDG 12 targets (Sustainable Production and Consumption) in our variable of SDG performance. To measure the firms’ social-innovation performance and eco-innovation performance, the study used five items each, representing the SDG 8 and SDG 12 targets, respectively. The social-innovation performance items were related to improving employee health and safety, increasing total employment, increasing qualified employment, maintaining existing employment, and compliance with health and safety regulations, as well as environmental ones. On the other hand, the eco-innovation performance items were related to reducing environmental impact, lower energy consumed per unit, lower materials employed per unit, higher production or service provision flexibility, and higher production or service provision capacity. The reliability of social-innovation performance and eco-innovation performance was measured using Cronbach’s alpha, which resulted in α = 0.71 and α = 0.88, respectively. A second-order two-factor model was employed to determine the adequacy of these measures, which showed a good fit with the data.
根據 PITEC(例如,Sáez-Martínez 等人,2016 年)或 CIS(例如,Ghisetti 等人,2015 年),在我們的社會創新代理中衡量可持續發展目標 8 具體目標(體面工作和經濟增長),並在我們的可持續發展目標績效變數中衡量與 SDG 12 具體目標(可持續生產和消費)相關的專案。為了衡量公司的社會創新績效和生態創新績效,該研究分別使用了五個項目,分別代表 分別是 SDG 8 和 SDG 12 的具體目標。社會創新績效專案與改善員工健康和安全、增加總就業、增加合格就業、維持現有就業以及遵守健康和安全法規以及環境法規有關。另一方面,生態創新績效專案與減少環境影響、降低單位能耗、減少單位使用的材料、提高生產或服務提供靈活性以及提高生產或服務提供能力有關。使用 Cronbach 的 alpha 測量社會創新績效和生態創新績效的可靠性,結果分別為 α = 0.71 和 α = 0.88。採用二階雙因素模型來確定這些措施的充分性,該模型與數據擬合良好。

To control potential confounding variables, we included several control variables in our analyses. Specifically, we controlled for firm age (i.e., length of time since company establishment), firm size (i.e., number of employees), and innovation strategy. Previous studies (e.g., Jansen et al., 2006) indicated the importance of distinguishing between exploration innovation (α = 0.87, F (555, 1351) = 3.23, p < 0.001) and exploitation innovation (α = 0.79, F(555, 1351) = 4.03, p < 0.001) as two innovation strategies. We also controlled for absorptive capacity (α = 0.91, F(555, 1351) = 2.21, p < 0.001) to exclude the impact of the ability to acquire, assimilate, transform, and exploit potential knowledge on firm alliance management capability (Jansen et al., 2005). Also, we controlled for environmental dynamism (α = 0.72, F (555, 1351) = 3.17, p < 0.001) to exclude the influence of a firm’s external environment on firm alliance management capability (e.g., Karagozoglu and Brown, 1988). Finally, we controlled industry (manufacturing and service sectors) in the study.
為了控制潛在的混雜變數,我們在分析中納入了幾個控制變數。具體來說,我們控制了公司年齡(即公司成立以來的時間長度)、公司規模(即員工人數)和創新戰略。以前的研究(例如,Jansen 等人,2006 年)表明區分勘探創新 (α = 0.87, F(555, 1351) = 3.23, p < 0.001) 和開發創新 (α = 0.79, F(555, 1351) = 4.03, p < 0.001) 作為兩種創新策略的重要性。 我們還控制了吸收能力 (α = 0.91, F(555, 1351) = 2.21, p < 0.001),以排除獲取、吸收、轉化和利用潛在知識的能力對公司聯盟管理能力的影響 (Jansen et al., 2005)。 此外,我們控制了環境動態性 (α = 0.72, F(555, 1351) = 3.17, p < 0.001),以排除公司外部環境對公司聯盟管理能力的影響(例如,KaragozogluBrown,1988)。最後,我們在研究中控制了工業(製造業和服務業)。

Common method bias test
常用方法偏差測試

To test for ex-post CMB, we conducted a Harman one-factor test, a widely accepted approach for testing the potential for CMB (Podsakoff et al., 2003). The results from the analysis demonstrated that the risk of CMB was not a significant concern, as eight factors were extracted with eigenvalues greater than one, but no one factor explained most of the variance. Furthermore, all the extracted factors accounted for 66.78% of the total variance, while a single-factor model accounted for only 12.53% of the variance, which was well below the maximum threshold of 50%. The poor factor loadings of all measurement items onto the single construct also confirmed that CMB was not a significant issue.
為了測試事後 CMB,我們進行了 Harman 單因素測試,這是一種被廣泛接受的測試 CMB 潛力的方法(Podsakoff 等人,2003 年)。分析結果表明,CMB 的風險不是一個顯著的問題,因為提取了8個特徵值大於1的因素,但沒有一個因素可以解釋大部分方差。此外,所有提取的因數佔總方差的 66.78%,而單因數模型僅占方差的 12.53%,遠低於 50% 的最大閾值。所有測量專案對單個結構的不良因數載荷也證實了CMB不是一個重要問題。

Additionally, we conducted confirmatory factor analysis (CFA) to test for CMB by including the measures for the four constructs of interest with maximum likelihood estimates. In the light of the causal direction being from constructs to items, and the items being highly interchangeable and correlated, reflective measures were used. We further followed the recommendations of Fitzgerald, Drasgow, Hulin, Gelfand, and Magley (1997) and Little, Rhemtulla, Gibson, and Schoemann (2013). We formed four item parcels for the following constructs, alliance management capability, business model innovation, and SDG performance, in order to produce stable parameter results (Kishton and Widaman, 1994; Landis, Beal, and Tesluk, 2000; Smith, Amiot, Callan et al., 2012), and to make sure the data more closely approximate a normal distribution (i.e., better quality, Bandalos and Finney, 2001; Hau, Wen, and Cheng, 2004). Original items were used for strategic flexibility (5 items). The analysis indicated that the proposed model had acceptable fit (χ2 = 590.49, df = 113, p < 0.001, RMSEA = 0.05 ≤ 0.08, CFI = 0.97 ≥ 0.90, TLI = 0.97 ≥ 0.90; Table 1)
此外,我們進行了驗證性因數分析 (CFA) 以通過包括具有最大似然估計的四種感興趣結構的測量來檢驗 CMB。鑒於因果方向是從結構到物品,並且物品具有高度可互換性和相關性,因此使用了反射措施。我們進一步遵循了 Fitzgerald、Drasgow、Hulin、Gelfand 和 Magley (1997) 以及 Little、Rhemtulla、Gibson Schoemann (2013) 的建議。我們為以下結構、聯盟管理能力、商業模式創新和 SDG 績效形成了四個專案包,以產生穩定的參數結果(KishtonWidaman,1994;Landis、Beal Tesluk,2000 年;Smith, Amiot, Callan et al., 2012),並確保數據更接近正態分佈(即品質更好,Bandalos Finney,2001 年; Hau, 溫, Cheng, 2004)。原始專案用於戰略靈活性(5 項)。分析表明,所提出的模型具有可接受的擬合 χ2 = 590.49,df = 113,p < 0.001,RMSEA = 0.05 ≤ 0.08,CFI = 0.97 ≥ 0.90,TLI = 0.97 ≥ 0.90;表 1)

The nested model comparisons have led to the rejection of the potential CMB. For example, in the CFA process, if all the items were included in a single construct, this one-factor model results in poor fit (χ2 = 8470.40, df = 119, p = 0.001, RMSEA = 0.19 > 0.08, CFI = 0.51 < 0.90, TLI = 0.44 < 0.90; Table 1). Discriminant validity tests indicated that the proposed model had the best fit, further validating that CMB is not an issue in this study.
嵌套模型比較導致對潛在 CMB 的拒絕。例如,在 CFA 過程中,如果所有專案都包含在單個構建體中,則此單因素模型會導致擬合不良 (χ2 = 8470.40,df = 119,p = 0.001,RMSEA = 0.19 > 0.08,CFI = 0.51 < 0.90,TLI = 0.44 < 0.90;表 1)。判別有效性檢驗表明,所提出的模型具有最佳擬合,進一步驗證了CMB不是本研究中的問題。

[Insert Table 1 here]
[在此處插入表 1]

Still, to minimize the potential for CMB, a partial correlation procedure was utilized after hypothesis testing to examine an appropriate marker variable (i.e., achievement of work-life balance). The procedure involved removing the correlations of theoretically unrelated and uncorrelated variables from the study variables, and the results showed no differences between the original findings and those obtained after using the partial correlation procedure (Online Appendix Table 1, Table 2 and Table 3). The paths retained their statistical significance, the direction remained unchanged, and there was negligible to no deviation in regression coefficients or z-values. These results suggest that CMB was absent or negligible and unlikely to have biased the study’s findings, providing further confidence in the results.
儘管如此,為了最大限度地減少 CMB 的可能性,在假設檢驗後使用偏相關程式來檢查適當的標誌變數(即,實現工作與生活平衡)。該程式涉及從研究變數中刪除理論上不相關和不相關變數的相關性,結果顯示原始發現與使用偏相關程式后獲得的結果之間沒有差異(在線附錄表 1、表 2 和表 3)。路徑保持其統計顯著性,方向保持不變,並且回歸係數或 z 值存在可忽略不計或沒有偏差。這些結果表明 CMB 不存在或可以忽略不計,並且不太可能使研究結果產生偏倚,從而為結果提供了進一步的可信度。

Results
結果

Correlation matrix and descriptive statistics are shown in Table 2. Before we move on to test our hypotheses, we have to make sure that the individual-level data can be aggregated to the firm level for hypotheses testing. We have adopted a multiple-informant approach in our survey. That means that we can arrive at ICC1, ICC2 and Rwg for each of our focal constructs and control variables. As shown in Table 3, all ICC1s, ICC2s and Rwgs are satisfactory. We then aggregate all the study and control variables into the firm level for hypotheses testing.
相關矩陣和描述性統計量如表 2 所示。在我們繼續測試我們的假設之前,我們必須確保個人層面的數據可以匯總到公司層面以進行假設檢驗。我們在調查中採用了多線人方法。這意味著我們可以得出每個焦點構建體和控制變數的 ICC1、ICC2 和 Rwg。如表 3 所示,所有 ICC1、ICC2 和 Rwgs 均令人滿意。然後,我們將所有研究和控制變數匯總到公司層面進行假設檢驗。

[Insert Table 2 & 3 here]
[在此處插入表2和表3]

Main analysis
主要分析

Multiple regression analysis was conducted to test the hypotheses, and multiplicative interaction terms were computed to examine moderation effects. To avoid potential multicollinearity, the constructs involved in the interaction terms were mean-centred. To check for mediation and moderation effects as well as robustness, the computational tool, PROCESS macro, facilitates the examinations (Preacher, Rucker, and Hayes, 2007; Hayes, 2022). The program calculated the 95% bias-corrected bootstrap confidence intervals of the mediation and interactions based on 5000 bootstrap samples. Previous research has used the same approach to test mediation and moderation hypotheses (e.g., Ahsan et al., 2023; Breugst et al., 2012; Huang et al., 2019; Oo et al., 2019), and this approach has proven to be robust. This approach allows us to test our direct and indirect as well as conditional indirect effect through bootstrapping. For each indirect effect and conditional effect as well as conditional indirect effect, the bootstrapped estimates and their corresponding 95% low and upper confidence intervals are reported.
進行多元回歸分析以檢驗假設,並計算乘法交互項以檢驗調節效應。為避免潛在的多重共線互項中涉及的結構以均值為中心。為了檢查中介和調節效應以及穩健性,計算工具 PROCESS 巨集促進了檢查(Preacher、Rucker 和 Hayes,2007 年;Hayes,2022 年)。該程式根據 5000 個 bootstrap 樣本計算了仲介和互動的 95% 偏差校正 bootstrap 置信區間。 以前的研究使用相同的方法來檢驗中介和調節假設(例如,Ahsan 等人,2023 年; Breugstet al., 2012;Huang et al., 2019; Ooet al., 2019),這種方法已被證明是穩健的。這種方法允許我們通過 bootstrap 測試我們的直接和間接以及有條件的間接影響對於每個間接效應和條件效應以及條件間接效應報告了靴束帶估計值及其相應的 95% 低濃度和上限濃度

H1 posited a positive relationship between firms’ alliance management capability and their SDG performance. Regression Model 3 (PROCESS macro Model 4) indicated a significant relationship (b = 0.45 , p< 0.001, Table 4), providing support for H1.
H1 假設公司的聯盟管理能力與其 SDG 績效之間存在正相關關係。回歸模型 3 (PROCESS 巨集模型 4) 表明存在顯著關係 (b = 0.45 p< 0.001,表 4),為 H1 提供支援。

[Insert Table 4 here]
[在此處插入表4]

H2 proposed that firms’ business model innovation mediates the relationship between their alliance management capability and SDG performance. Regression Model 4 (PROCESS macro Model 4) indicated a significant relationship (b = 0.24, p < 0.01, Table 4 ), providing support for H2. Further analysis revealed significant effect coefficients for the total, direct, and indirect effects, with no zero values in the bootstrapped 95% confidence interval range, indicating a significant mediation effect. Therefore, the mediating effect of business model innovation is supported.
H2 提出,企業的商業模式創新在其聯盟管理能力與 SDG 績效之間的關係之間起仲介作用。回歸模型 4 (PROCESS 巨集模型 4) 表明存在顯著關係 (b= 0.24,p < 0.01,表 4),為 H2 提供支援。進一步分析顯示,總效應、直接效應和間接效應均具有顯著效應係數,在自舉的 95% 置信區間範圍內沒有零值,表明存在顯著的中介效應。因此,支援商業模式創新的中介效應

H3 predicted that the positive relationship between firms’ alliance management capability and their business model innovation is moderated by strategic flexibility. Regression Model 2 (PROCESS macro Model 58) revealed that strategic flexibility moderates the effect between firms’ alliance management capability and business model innovation and thus supported this hypothesis (b = 0.23, p < 0.01, Table 4). The analysis of conditional values for low (-1 standard deviation), mean, and high (+1 standard deviation) values of strategic flexibility provided more detailed insights into this interaction effect. At high values (b = 0.13; p < 0.001, Table 5), there was a significant positive effect on the relationship between firms’ alliance management capability and their business model innovation. However, no effect was observed at low levels. Thus, the relationship between firms’ alliance management capability and their business model innovation was shown to strengthen at increasingly higher levels of strategic flexibility. Figure 2 presents the interaction plot.
H3 預測,公司的聯盟管理能力與其商業模式創新之間的正相關關係受到戰略靈活性的調節。回歸模型 2 (PROCESS 巨集觀模型 58) 顯示,戰略靈活性調節了公司的聯盟管理能力與商業模式創新之間的影響,因此支援了這一假設 (b = 0.23, p < 0.01, 表 4)。對戰略靈活性的低值(-1 個標準差)、平均值和高值(+1 個標準差)的條件值進行了分析,為這種交互效應提供了更詳細的見解。在高值 (b = 0.13; p < 0.001,表 5),對企業聯盟管理能力與其商業模式創新之間的關係存在顯著的正向影響。然而,在低水平下沒有觀察到任何影響。因此,公司的聯盟管理能力與其商業模式創新之間的關係被證明在越來越高水平的戰略靈活性下得到加強。 圖 2 顯示了互動作用圖。

[Insert Table 5 & Figure 2 here]
[在此處插入表5和圖2]

H4 posited that the positive relationship between firms’ business model innovation and their SDG performance is moderated by strategic flexibility. Regression Model 4 (PROCESS macro Model 1) showed that strategic flexibility moderates the relationship between firms’ business model innovation and their SDG performance and thus supported this hypothesis (b = 0.90; p < 0.001). Further analysis of the conditional values for low (-1 standard deviation), mean, and high (+1 standard deviation) values of strategic flexibility reveal more detailed insights into this interaction effect. At high values (b = 0.48, p < 0.001, Table 5), there was a significant positive effect of strategic flexibility on the relationship between firms’ business model innovation and their SDG performance. No effect was observed at low levels. These findings suggest that the relationship between firms’ business model innovation and SDG performance is strengthened at increasingly higher levels of strategic flexibility. Figure 3 presents the interaction plot.
H4 認為,公司的商業模式創新與其 SDG 績效之間的正相關關係受到戰略靈活性的調節。回歸模型 4(PROCESS 巨集觀模型 1)表明,戰略靈活性調節了公司的商業模式創新與其 SDG 績效之間的關係,因此支援了這一假設 (b = 0.90; p < 0.001).進一步分析戰略靈活性的低值(-1 個標準差)、平均值和高值(+1 個標準差)的條件值,可以更詳細地瞭解這種交互效應。在高值(b = 0.4 8,p < 0.001,表 5)下,戰略靈活性對公司的商業模式創新與其可持續發展目標績效之間的關係存在顯著的積極影響。在低水準下未觀察到任何影響。這些發現表明,企業商業模式創新與 SDG 績效之間的關係在戰略靈活性水平越來越高的情況下得到加強。 圖 3 顯示了互動作用圖。

[Insert Table 6& Figure 3 here]
[在此處插入表格6和圖3]

H5 proposed that strategic flexibility would positively moderate the indirect effect of firms’ alliance management capability on their SDG performance via business model innovation. Regression Model 6 (PROCESS macro Model 58) showed that this is the case and thus supported this hypothesis (b = 0.58; p < 0.001, Table 4). Further analysis of the conditional values for low (-1 standard deviation), mean, and high (+1 standard deviation) values of strategic flexibility provided insights into this interaction effect. At high values (b = 0.29; p < 0.001, Table 7), there was a significant positive effect of on firms’ alliance management capabilities on their SDG performance. No effect was observed at low levels. Therefore, the indirect relationship between firms’ alliance management capability and their SDG performance was found to strengthen at increasingly higher levels of strategic flexibility. 

[Insert Table 7 here] 

20 

5.2. Post-hoc analysis 

To further assess the robustness of the model, the PROCESS macro was used to analyse the two sub-dimensions of SDG performance, namely social innovation performance and eco-innovation performance.  

Specifically, Regression Models 1 to 5 in Table 8 provided further support for H1 to H5 using social innovation performance as the dependent variable. Furthermore, analysing the conditional values under Mplus for low (-1 standard deviation), mean, and high (+1 standard deviation) values of strategic flexibility offered finer-grained insights into this interaction effect (Table 9 and Table 10). 

[Insert Table 8, Table 9, and Table 10 here] 

Similarly, Regression Models 1 to 5 in Table 11 further support H1 to H5 using eco-innovation performance as dependent variable. Moreover, analysing the conditional values under Mplus for low (-1 standard deviation), mean, and high (+1 standard deviation) values of strategic flexibility provided finer-grained insights into this interaction effect (Table 12 and Table 13).  

[Insert Table 11, 12 and 13 here] 

5.3. Robustness check 

We also run the analysis to test the strategic flexibility as a potential mediator. The results of Table 14 show that the indirect effect of strategic flexibility is not significant (b = -0.00, p>0.05, Table 14). Hence, the strategic flexibility as a potential mediator is unlikely to occur and potential mediation-moderation does not exist in this study. 

[Insert Table 14] 

6. Discussion 

Strategic alliances are crucial for sustainable development, yet managing these partnerships effectively to maximise their benefits presents a complex challenge. Scholars often debate the optimal management of strategic alliances to enhance their efficiency and contribution to SDGs (e.g., Al-Tabbaa et al., 2023; Bouncken et al., 2022; Bouncken et al., 2020; Foroudi et al., 2023; Vurro et al., 2024). This study investigates whether a firm's ability to manage alliances can aid its pursuit of SDGs, particularly through the lens of business model innovation. Our findings indicate that alliance management capabilities directly enhance performance towards SDG 8 and SDG 12, and this relationship is further mediated by business model innovation. Additionally, strategic flexibility plays a moderating role, influencing both the direct impact of alliance management capabilities on business model innovation and the mediated effect on SDG performance. This research contributes to the ongoing discussion, highlighted by Gillani et al. (2023), van Gestel et al. (2024) and Vurro et al. (2024), on how alliance management capabilities can foster sustainable development within dynamic environments (Arndt et al., 2022). 

Theoretical contributions 

Our study extends the relational view theory by revealing the pivotal role of alliance management capabilities in maintaining quality employment and catalysing resource efficiency to achieve SDGs (Martinez et al., 2019). We deepen the understanding of how inter-organisational collaboration can effectively contribute to sustainability transitions and enrich the discourse on the antecedents of SDG achievement as a competitive advantage within firms. This responds to the call by Jiang et al. (2021) for more nuance studies regarding the interplay between organisational strategies and sustainable outcomes. At this same time, this clarifies that resources acquired from partnerships can generate competitive advantages more effectively when they are well-managed and integrated. In line with the prior research which has established the importance of alliances in sustainability (Lozano, 2007; Quintana-García et al., 2021; Riegler et al., 2023; Schneider & Clauß, 2020; Williams & Blasberg, 2022), our study advances the relationship by empirically validating how alliance management capabilities enhance the efforts placing in alliances. This focus on internal capabilities shifts the narrative from simply examining the roles of external partners to a deeper exploration of how alliance management capabilities crucially influence the success of sustainability-oriented alliances. Moreover, we reveal that business model innovation serves as a critical mediator between alliance management capabilities and SDG performance, while strategic flexibility enhances the impact of these capabilities on business model innovation and, ultimately, on SDG performance. This underscores the dynamic interplay between strategic flexibility and business model innovation in aiding organisations to meet their sustainability goals, particularly SDGs 8 and 12. Our findings offer a more comprehensive model that incorporates internal organisational attributes into the broader narrative of sustainability transitions, filling a notable gap in the literature by melding strategic management theory with sustainability research. Consequently, this opens up a new interdisciplinary avenue for scholarly investigation that explores the synergies between internal capabilities and external collaborations in driving sustainability goals. Through this, our study provides valuable strategies for firms aiming to optimise alliances for sustainable growth and deepens insights into how relational rents are generated through strategic partnerships. 

Second, our research accentuates the importance of business model adjustments to facilitate sustainability transition. While existing literature (Pedersen et al., 2018; Schneider & Clauß, 2020; Spieth et al., 2019) establishes the transformative role of business model innovation within organisations, our work goes further by empirically demonstrating its critical role in leveraging the opportunities that come from alliances. This is pivotal because business models are not static but dynamic frameworks that evolve over time and in response to varied externalities (Arndt, 2019). We show that business model innovation is not merely an optional but a crucial mechanism for maintaining quality employment and resource efficiency within firms. It serves as a conduit that helps firms not only adapt to but capitalize on the beneficial aspects of their alliances, thereby making a more effective and impactful stride toward achieving SDG 8 and SDG 12. We argue that business model innovation can act as the operational ‘glue’ that integrates the advantages of alliances into a firm’s sustainability strategy. This view significantly enhances our understanding of the operational intricacies involved in achieving a sustainable transition and offers a nuanced perspective that integrates external alliance opportunities with internal transformative strategies.
其次,我們的研究強調了商業模式調整對促進可持續發展轉型的重要性雖然現有文獻(Pedersen et al., 2018;Schneider & Clauß,2020 年;Spieth et al., 2019)確立了商業模式創新在組織內的變革作用,我們的工作通過實證證明其在利用聯盟帶來的機會方面的關鍵作用而走得更遠。這一點至關重要,因為商業模式不是靜態的,而是動態的框架,它們會隨著時間的推移而發展,並回應不同的外部因素(Arndt,2019)。我們表明,商業模式創新不僅僅是一種可選,而是維持公司內部優質就業和資源效率的重要機制。它作為一個管道,説明公司不僅適應而且利用其聯盟的有益方面,從而朝著實現 SDG 8 和 SDG 12 邁出更有效和有影響力的一步。我們認為,商業模式創新可以充當運營「膠水」,將聯盟的優勢整合到公司的可持續發展戰略中。這一觀點顯著增強了我們對實現可持續轉型所涉及的運營複雜性的理解,並提供了一個微妙的視角,將外部聯盟機會與內部轉型戰略相結合。

Third, our study makes a significant contribution to the emerging discussion on collaborative business model innovation (Bouncken & Fredrich, 2016a; Spieth et al., 2021; Velu, 2015). While existing research confirms the benefits of external knowledge and partnerships in the process of business model innovation, our study advances this understanding by emphasizing the necessity of internal capabilities for managing these external relationships effectively. We empirically establish that merely having access to external knowledge is not enough; firms must possess the capabilities to manage their alliances to extract maximum value. This insight complements and extends the existing literature on the capabilities required for business model innovation (Clauss et al., 2021; Hock-Doepgen et al., 2020; Mezger, 2014; Teece, 2018) by introducing the notion of alliance management capability as a crucial factor. This integration suggests that future research in business model innovation needs to consider both external collaborative factors and internal management capabilities to provide a more nuanced understanding of how firms can leverage business model innovation for sustainable outcomes.
第三我們的研究對關於協作商業模式創新的 新興討論做出了重大貢獻(Bouncken & Fredrich,2016a; Spieth et al., 2021; Velu,2015 年)雖然現有研究證實了外部知識和合作夥伴關係在商業模式創新過程中的好處,但我們的研究通過強調有效管理這些外部關係的內部能力的必要性來推進這種理解。我們憑實證確定,僅僅獲得外部知識是不夠的;公司必須具備 管理其聯盟以獲取最大價值的能力。這一見解補充和擴展關於商業模式創新所需能力的現有文獻(Clauss et al., 2021;Hock-Doepgen et al., 2020;Mezger,2014 年;Teece,2018 年),通過將聯盟管理能力的概念作為一個關鍵因素引入。這種整合表明,未來的商業模式創新研究需要同時考慮外部協作因素和內部管理能力,以更細緻地理解公司如何利用商業模式創新實現可持續成果。

Last, our study advances the theoretical understanding of the role of strategic flexibility by demonstrating its moderating impact on the relationship between alliance management capability, business model innovation, and SDG performance. Traditional discussions have oscillated around whether strategic flexibility serves as an antecedent, a consequence, or a moderator in various contexts, including business model innovation. Our findings contribute to resolving this debate by providing empirical evidence that strategic flexibility acts as a significant moderating factor. Moreover, we enrich this debate by situating it within the context of SDG performance, an area where the role of strategic flexibility has been less explored. Building on the relational view (Dyer & Singh, 1998; Dyer, Singh, & Hesterly, 2018), our study posits that strategic flexibility can serve as an effective buffer mechanism in inter-organisational relationships. It does so by enabling firms to adjust their formal and informal knowledge-exchange mechanisms dynamically, which in turn allows them to maximize relational rents. These rents are crucial in that they provide a competitive edge in achieving better SDG performance. Our work suggests that strategic flexibility not only aids in internal capability development—such as alliance management capability—but also magnifies the returns from these capabilities by optimizing their application in varied contextual settings, in this case, SDG performance. Additionally, strategic flexibility enhances a firm’s ability to respond to volatile external conditions, such as market disruptions and/or regulatory changes, which are particularly pertinent when working towards SDGs that are impacted by a multitude of complex factors. Thus, in essence, strategic flexibility offers a dual advantage: it acts as a situational enhancer that maximizes the benefits derived from alliance management capability and business model innovation and serves as a resilience mechanism that helps firms navigate the complex and often volatile pathway to achieving SDGs.
最後,我們的研究通過證明戰略靈活性對聯盟管理能力、商業模式創新和SDG績效之間關係的調節影響,推進了對戰略靈活性作用的理論理解。傳統討論一直圍繞著戰略靈活性在各種情況下(包括商業模式創新)是前因、結果還是調節因素而搖擺不定。我們的研究結果通過提供經驗證據證明戰略靈活性是一個重要的調節因素,從而有助於解決這一爭論。此外,我們通過將 SDG 績效置於 SDG 績效的背景下來豐富這一辯論,而戰略靈活性的作用在該領域的作用尚未得到充分探索。建立在關係觀點之上(Dyer & Singh,1998;Dyer, Singh, & Hesterly, 2018),我們的研究假設戰略靈活性可以作為組織間關係中的有效緩衝機制。它通過使公司能夠動態地調整其正式和非正式的知識交流機制來實現這一點,這反過來又使它們能夠最大化關係租金。這些租金至關重要,因為它們為實現更好的可持續發展目標提供了競爭優勢。我們的研究表明,戰略靈活性不僅有助於內部能力發展(例如聯盟管理能力),還可以通過在各種背景下優化其應用(在本例中為 SDG 績效)來放大這些能力的回報。此外,戰略靈活性增強了公司應對波動的外部條件的能力,例如市場中斷和/或監管變化,這在努力實現受眾多複雜因素影響的可持續發展目標時尤為重要。 因此,從本質上講,戰略靈活性具有雙重優勢:它充當情境增強器,最大限度地利用聯盟管理能力和商業模式創新帶來的好處,並作為一種彈性機制,説明公司駕馭複雜且往往不穩定的實現可持續發展目標的道路。

Managerial Implication  

The first is to invest in alliance management capability. Our findings underscore the importance of developing and leveraging alliance management capabilities for enhancing SDG performance. Firms should not just seek partnerships but invest in the internal resources and mechanisms required to manage these alliances effectively. This entails setting up dedicated teams or units responsible for alliance governance, conflict resolution, and knowledge exchange. It is not just about forming partnerships; it is about managing them in a way that aligns with sustainability objectives. Through effective alliance management, firms can maximise the relational rents and collaborative advantages that come from interorganisational cooperation, thereby directly enhancing their contributions to the SDGs. 

The second is to prioritise business model innovation. Our research suggests that business model innovation serves as a vital mediator in the relationship between alliance management capability and SDG performance. Managers should, therefore, be proactive in adapting their business models to integrate sustainability objectives and leverage external inputs from alliances. This could involve the redesign of products or services, rethinking supply chains, or creating new customer engagement strategies that align with SDGs. It is about using the innovative capabilities of the organisation, honed through alliances, to deliver meaningful and sustainable impact. Investing in R&D and establishing cross-functional teams could be steps in facilitating this type of innovation. 

The third is to nurture strategic flexibility. Strategic flexibility emerges as a key moderating factor that can enhance the effectiveness of both alliance management capability and business model innovation in contributing to SDG performance. Managers should view strategic flexibility not merely as a contingency plan but as an inherent organisational capability. This means embedding flexibility into decision-making processes, organisational culture, and even contractual terms in alliances. In a rapidly changing world beset with challenges ranging from market volatility to regulatory shifts, strategic flexibility enables firms to pivot quickly, adapting both their internal strategies and external alliances to meet emerging sustainability goals. By doing so, firms can optimize their alliance portfolios and adapt their business models in response to evolving sustainability challenges, thus maximizing their SDG performance. 

Furthermore, in the light of the strengthening effect of strategic flexibility on the relationship between business model innovation and SDG performance, we advise that strategic flexibility is one key enabling condition for the effect of business model innovation on SDG performance. Business model innovation is in and of itself a contributing factor to a firm’s competitive advantage. At the same time, the pursuit of SDG performance demands the firm to be innovative in its business model so that the firm can fully capitalize on its innovative business model, apart from economic rents. Strategic flexibility plays a key role in helping the firm achieve SDG performance for long-term sustainability, in addition to short-term financial gains, given the firm’s innovative business model. 

Notwithstanding the above key takeaways and noteworthy contributions, this study remains limited in several ways. First, this study is limited to evidence from large firms in Taiwan and thus future research should seek alternative evidence from small firms and other developing and developed countries to either reaffirm or refute the findings herein this study. Second, this study only considered alliance management capability, business model innovation, and strategic flexibility as a macro construct and thus future research can explore the specific dimensions of these constructs (e.g., the reactive versus proactive and the offensive versus defensive manifestations of strategic flexibility; Brozovic, 2018) to provide finer-grained insights that would extend the richness of the findings herein this study. 

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20

Figure 1. Conceptual model

20

Table 1 Comparisons of measurement models

Model

No. of factors

χ2

df

χ2

df

RMSEA

CFI

TLI

Baseline

Foura

590.49

113

-

-

.05

.97

.97

1

Threeb

3780.80

116

3190.31***

3

.13

.78

.75

2

Threec

2600.11

116

2009.62***

3

.11

.85

.83

3

Threed

3337.81

116

2747.32***

3

.12

.81

.78

4

Threee

3681.89

116

3091.40***

3

.13

.79

.75

5

Threef

3725.99

116

3135.50***

3

.13

.79

.75

6

Threeg

3208.07

116

2617.58***

3

.12

.82

.79

7

Twoh

5768.71

118

5178.22***

5

.16

.67

.62

8

Twoi

6514.42

118

5923.93***

5

.17

.62

.56

9

Twoj

6515.31

118

5924.82***

5

.17

.62

.56

10

Twok

6262.11

118

5671.62***

5

.17

.64

.58

11

Onel

8470.40

119

7879.91***

6

.19

.51

.44

Notes: a alliance management capability (AMC); business model innovation (BMI); strategic flexibility (SF); SDG performance (SDG).

b Three factors: AMC combined with BMI; SF; SDG.

c Three factors: AMC combined with SF; BMI; SDG.

d Three factors: AMC combined with SDG; BMI; SF.

e Three factors: BMI combined with SF; AMC; SDG.

f Three factors: BMI combined with SDG; AMC; SF.

g Three factors: SF combined with SDG; AMC; BMI.

h Two factors: AMC, BMI and SF combined; SDG.

i Two factors: AMC, BMI and SDG combined; SF.

j Two factors: AMC, SF and SDG combined; BMI.

k Two factors: BMI, SF and SDG combined; AMC.

l One factor: all four variables combined.

* p < .05, ** p < .01, *** p < .001.

Table 2. Correlation matrix and descriptive statistics

Variables

Mean

SD

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

1

Manufacturing

.56

.50

-

2

Firm age

9.58

3.90

-.46***

-

3

Firm size

663.67

327.37

.02

.11**

-

4

Exploration

3.93

.34

-.03

-.07

-.20***

-

5

Exploitation

3.80

.37

-.04

-.08

-.23***

.50***

-

6

Environmental dynamism

3.91

.40

-.02

-.02

-.09*

.43***

.25***

-

7

Absorptive capacity

3.86

.32

.04

.03

.17***

-.03

.01

-.02

-

8

Past performance

-0.00

.05

.08

.05

.03

-.03

.02

.01

.07

-

9

Environmental Vitality

4.09

.65

.14**

-.05

.12**

.00

.01

.01

.01

-.02

-

10

Competitive Intensity

4.19

.47

-.05

.37***

.08

-.01

-.03

-.02

.00

.09*

-.04

-

11

Alliance management capability

3.99

.47

.06

-.00

-.03

.06

.09*

.06

-.04

.09*

.14**

.05

-

12

Strategic flexibility

4.37

.26

.01

.02

.01

-.04

.02

-.06

.05

.65***

-.06

-.02

.08

-

13

Business model innovation

3.99

.27

.02

-.04

-.08

.16***

.25***

.09*

-.01

.18***

-.03

.03

.12**

.20***

-

14

SDG performance

.42

.42

.05

-.01

.02

.03

.09*

.00

-.01

.06

.00

-.00

.51***

.09*

.18***

-

15

Social innovation performance

3.78

.30

.02

-.00

-.02

.02

-.01

.02

.06

.11*

-.04

-.03

.13**

.16**

.14**

.10*

-

16

Eco innovation performance

4.07

.49

-.03

-.01

-.00

-.04

.03

-.04

.07

.08

-.01

-.02

.11*

.11**

.14**

.13***

.20***

-

Note:* p < .05; ** p < .01; *** p < .001. SD: Standard deviation. N = 556

Table 3. ICCs and Rwgs of Variables

Variables

ICC1

ICC2

Rwg

Alliance management capability

0.27

0.55

0.95

Strategic flexibility

0.22

0.49

0.85

Business model innovation

0.16

0.39

0.93

Social innovation performance

0.15

0.38

0.85

Eco-innovation performance

0.16

0.40

0.85

Exploration

0.39

0.69

0.89

Exploitation

0.47

0.75

0.89

Environmental dynamism

0.39

0.68

0.85

Absorptive capacity

0.26

0.55

0.96

Environmental Vitality

0.45

0.84

0.87

Competitive Intensity

0.80

0.96

0.97

Table 4. Main analysis regression results: SDG performance

Variables

Model 1

Business model innovation (PROCESS macro Model 4)

Model 2

Business model innovation (PROCESS macro Model 58)

Model 3

SDG performance (PROCESS macro Model 4)

Model 4

SDG performance

(PROCESS macro Model 1)

Model 5

SDG performance (PROCESS macro Model 4)

Model 6

SDG performance (PROCESS macro Model 58)

Control and industry dummy variables

Manufacturing

-0.00 (-0.22)

[-0.03,0.02]

0.00 (0.07)

[-0.02,0.03]

0.01 (0.42)

[-0.03, 0.04]

0.02 (1.14)

[-0.00, 0.06]

0.01 (0.66)

[-0.01,0.03]

0.01 (0.50)

[-0.01,0.04]

Firm age

-0.01 (-0.70)

[-0.03, 0.01]

-0.01 (-0.45)

[-0.03,0.02]

0.00 (0.01)

[-0.03, 0.04]

0.01 (0.61)

[-0.02,0.05]

0.00 (0.09)

[-0.03,0.03]

0.00 (0.21)

[-0.02,0.03]

Firm size

-0.00 (-0.25)

[-0.03,0.02]

-0.00 (-0.28)

[-0.03,0.02]

0.02 (1.28)

[-0.01, 0.05]

0.02 (1.09)

[-0.01,0.06]

0.02 (1.31)

[-0.00, 0.05]

0.02 (1.37)

[-0.00,0.06]

Exploration

0.01 (0.97)

[-0.02,0.04]

0.02 (1.27)

[-0.01,0.05]

-0.01 (-0.34)

[-0.04,0.03]

-0.01 (-0.26)

[-0.04,0.02]

-0.01 (-0.45)

[-0.04,0.01]

-0.01 (-0.35)

[-0.04,0.02]

Exploitation

0.06 (4.38)***

[0.03, 0.08]

0.06 (4.29)***

[0.03, 0.08]

0.03 (1.53)

[-0.01,0.06]

0.03 (1.60)

[-0.01,0.09]

0.02 (1.04)

[-0.01,0.06]

0.02 (1.19)

[-0.01,0.07]

Environmental dynamism

0.00 (0.08)

[-0.02,0.02]

0.00 (0.08)

[-0.02,0.03]

-0.01 (-0.79)

[-0.05,0.02]

-0.01 (-0.32)

[-0.03,0.02]

-0.01 (-0.80)

[-0.04 0.00]

-0.01 (-0.07)

[-0.04,0.00]

Absorptive capacity

-0.00 (-0.31)

[-0.03,0.02]

-0.00 (-0.32)

[-0.03,0.02]

-0.00 (-0.04)

[-0.03,0.03]

-0.01 (-0.73)

[-0.03,0.01]

-0.00 (-0.01)

[-0.01,0.01]

-0.00 (-0.13)

[-0.02,0.01]

Past performance

0.95 (4.02)***

[0.53, 1.50]

0.52 (1.66)

[-0.07, 1.10]

0.13 (0.40)

[-0.52,0.78]

0.32 (0.61)

[-0.15,0.85]

-0.01 (-0.04)

[-0.26,0.27]

-0.29 (-0.64)

[-0.77, 0.02]

Direct effects

Alliance management capability

0.07 (2.96)**

[0.02, 0.11]

0.07 (2.84)**

[0.02, 0.11]

0.45 (13.67)***

[0.39, 0.52]

0.44 (13.28)***

[0.33, 0.57]

0.43 (13.09)***

[0.33,0.56]

Strategic flexibility

0.15 (2.76)**

[0.04, 0.26]

0.10 (1.10)

[-0.04,0.27]

0.16 (2.02)*

[0.04,0.32]

Business model innovation

0.24 (3.57)**

[0.10,0.43]

0.15 (2.58)*

[0.04, 0.30]

0.14 (2.30)*

[0.10,1.26]

Interaction effects

Alliance management capability × Strategic flexibility

0.23 (2.58)**

[0.06, 0.41]

Business model innovation × Strategic flexibility

0.90(3.89)***

[0.32,1.68]

0.58 (2.85)**

[0.18,0.98]

Regression model statistics

R2

0.***

0.14***

0.27***

0.07***

0.28***

0.30***

Mediation analysis

Effect coefficient

Standard error

t-value

(X = Alliance management capability; Y= SDG performance; M = Business model innovation; 5,000 bootstraps):

Direct effect of X on Y

0.44***

[0.33, 0.58]

0.03

13.28

Indirect effect of X on Y by M

0.01*

[0.002, 0.03]

Total effect of X on Y

0.45*

Direct effect of X on M

0.07**

[0.02, 0.11]

0.02

2.96

Standardized indirect effect b

0.01*

[0.003, 0.02]

Conclusion of R test

Mediation effect: Confirmed

Notes: We report unstandardized regression coefficients with t-values in parentheses. Values in square brackets represent bootstrapped 95% confidence interval values (unstandardized coefficients) [LL, UL].

* p < .05; ** p < 0.01; *** p < .001.

Table 5. Conditional effect of alliance management capability and business model innovation at values of the moderator (strategic flexibility)

Moderator: Strategic flexibility

Effect coefficient

t-value

95% CI [LL, UL]

-0.26

0.01

0.16

[-0.06, 0.07]

0.00

0.07**

2.84

[0.02, 0.11]

0.26

0.13***

4.06

[0.07, 0.19]

Notes: Values are -1 standard deviation, mean, +1 standard deviation.

* p < .05; ** p < 0.01; *** p < .001.

Table 6. Conditional effect of business model innovation and SDG performance at values of the moderator (strategic flexibility)

Moderator: Strategic flexibility

Effect coefficient

t-value

95% CI [LL, UL[

-0.26

0.00

0.04

[-0.18, 0.18]

0.00

0.24***

3.57

[0.11, 0.37]

0.26

0.48***

5.25

[0.30, 0.66]

Notes: Values are -1 standard deviation, mean, +1 standard deviation.

* p < .05; ** p < 0.01; *** p < .001.

Table 7. Conditional indirect effect of alliance management capability on SDG performance by business model innovation at values of the moderator (strategic flexibility)

Moderator: Strategic flexibility

Effect coefficient

t-value

95% CI [LL, UL]

-0.26

-0.02

-0.21

[-0.17, 0.14]

0.00

0.14*

2.30

[0.02, 0.25]

0.26

0.29***

3.59

[0.13, 0.45]

Notes: Values are -1 standard deviation, mean, +1 standard deviation.

* p < .05; ** p < 0.01; *** p < .001.

Table 8. Post-hoc analysis regression results: Social innovation performance

Variables

Model 1

Business model innovation (PROCESS macro Model 4)

Model 2

Business model innovation (PROCESS macro Model 58)

Model 3

Social innovation performance (PROCESS macro Model 4)

Model 4

Social innovation performance (PROCESS macro Model 1)

Model 5

Social innovation performance (PROCESS macro Model 4)

Model 6

Social innovation performance (PROCESS macro Model 58)

Control and industry dummy variables

Manufacturing

-0.00 (-0.22)

[-0.03,0.02]

0.00 (0.03)

[-0.02,0.03]

0.00 (0.01)

[-0.03,0.03]

0.00 (0.27)

[-0.02,0.03]

0.00 (0.04)

[-0.03,0.03]

0.00 (0.12)

[-0.03,0.03]

Firm age

-0.01 (-0.70)

[-0.03, 0.02]

-0.01 (-0.45)

[-0.03,0.02]

-0.00 (-0.20)

[-0.03,0.03]

0.00 (0.10)

[-0.03,0.03]

-0.00 (-012)

[-0.03,0.01]

0.00 (0.01)

[-0.02,0.03]

Firm size

-0.00 (-0.25)

[-0.03,0.02]

-0.00 (-0.28)

[-0.03,0.02]

-0.01 (-0.54)

[-0.03,0.02]

-0.01 (-0.50)

[-0.03,0.02]

-0.01 (-0.51)

[-0.03,0.02]

-0.01 (-0.48)

[-0.03,0.02]

Exploration

0.01 (0.97)

[-0.02,0.04]

0.02 (1.27)

[-0.01,0.05]

0.01 (0.69)

[-0.02,0.04]

0.01 (0.69)

[-0.02,0.04]

0.01 (0.58)

[-0.02,0.04]

0.01 (0.68)

[-0.02, 0.04]

Exploitation

0.06 (4.38)***

[0.03, 0.08]

0.06 (4.29)***

[0.03, 0.08]

-0.02 (-1.07)

[-0.04,0.01]

-0.02 (-1.32)

[-0.05,0.01]

-0.02 (-1.55)

[-0.05,0.01]

-0.02 (-1.45)

[-0.05,0.01]

Environmental dynamism

0.00 (0.08)

[-0.02,0.03]

0.00 (0.08)

[-0.02,0.03]

0.00 (0.14)

[-0.03,0.03]

0.00 (0.33)

[-0.02,0.03]

0.00 (0.13)

[-0.02,0.03]

0.00 (0.27)

[-0.02,0.03]

Absorptive capacity

-0.00 (-0.31)

[-0.03,0.02]

-0.00 (-0.32)

[-0.03,0.02]

0.02 (1.41)

[-0.01,0.04]

0.02 (1.22)

[-0.01,0.04]

0.02 (1.46)

[-0.01,0.04]

0.02 (1.36)

[-0.01,0.04]

Past performance

0.95 (4.02)***

[0.53, 1.47]

0.52 (1.66)

[-0.08, 1.13]

0.60 (2.24)**

[0.08,1.13]

0.26 (0.70)

[-0.46,0.98]

0.48 (1.77)

[-0.10,0.88]

0.17 (0.45)

[-0.52,0.75]

Direct effects

Alliance management capability

0.07 (3.04)**

[0.02, 0.12]

0.07 (2.84)**

[0.02, 0.11]

0.08 (2.99)**

[0.03,0.13]

0.07 (2.64)**

[0.02,0.12]

0.07 (2.45)*

[0.01,0.12]

Strategic flexibility

0.15 (2.76)**

[0.04, 0.26]

0.13 (2.11)*

[0.01,0.26]

0.14 (2.26)*

[0.03,0.26]

Business model innovation

0.13 (2.70)**

[0.04,0.22]

0.13 (2.66)**

[0.04,0.22]

0.11 (2.36)*

[0.02,0.21]

Interaction effects

Alliance management capability × Strategic flexibility

0.23 (2.58)*

[0.06, 0.40]

.

Business model innovation × Strategic flexibility

0.45 (2.73)**

[0.13,0.77]

0.40 (2.42)**

[0.11, 0.67]

Regression model statistics

R2

0.11***

0.14***

0.03*

0.06***

0.05**

0.07**

Mediation analysis

Effect coefficient

Standard error

t-value

(X = Alliance management capability; Y= Social innovation performance; M = Business model innovation; 5,000 bootstraps):

Direct effect of X on Y

0.07**

[0.02,0.12]

0.03

2.64

Indirect effect of X on Y by M

0.01*

[0.002, 0.02]

Total effect of X on Y

0.08*

Direct effect of X on M

0.07**

[0.02, 0.12]

0.02

3.04

Standardized indirect effect b

0.01*

[0.003, 0.03]

Conclusion of R test

Mediation effect: Confirmed

Notes: We report unstandardized regression coefficients with t-values in parentheses. Values in square brackets represent bootstrapped 95% confidence interval values (unstandardized coefficients) [LL, UL].

* p < .05; ** p < 0.01; *** p < .001.

Table 9. Conditional effect of business model innovation and social innovation performance at values of the moderator (strategic flexibility)

Moderator: Strategic flexibility

Effect coefficient

t-value

95% CI [LL, UL]

-0.26

0.01

0.18

[-0.12, 0.14]

0.00

0.13**

2.70

[0.04, 0.22]

0.26

0.25***

3.83

[0.12, 0.38]

Notes: Values are -1 standard deviation, mean, +1 standard deviation.

* p < .05; ** p < 0.01; *** p < .001.

Table 10. Conditional indirect effect of alliance management capability on social innovation performance by business model innovation at values of the moderator (strategic flexibility)

Moderator: Strategic flexibility

Effect coefficient

t-value

95% CI [LL, UL]

-0.26

0.01

0.13

[-0.12, 0.13]

0.00

0.11*

2.36

[0.02, 0.21]

0.26

0.22***

3.34

[0.09, 0.35]

Notes: Values are -1 standard deviation, mean, +1 standard deviation.

* p < .05; ** p < 0.01; *** p < .001.

Table 11. Post-hoc analysis regression results: Eco-innovation performance

Variables

Model 1

Business model innovation (PROCESS macro Model 4)

Model 2

Business model innovation (PROCESS macro Model 58)

Model 3

Eco-innovation performance (PROCESS macro Model 4)

Model 4

Eco-innovation performance (PROCESS macro Model 1)

Model 5

Eco-innovation performance (PROCESS macro Model 4)

Model 6

Eco-innovation performance (PROCESS macro Model 58)

Control and industry dummy variables

Manufacturing

-0.00 (-0.22)

[-0.03,0.02]

0.00 (0.03)

[-0.02,0.02]

-0.03 (-1.41)

[-0.08,0.01]

-0.03 (-1.26)**

[-0.08,0.02]

-0.03 (-1.40)

[-0.08,0.01]

-0.03 (-1.44)

[-0.08,0.02]

Firm age

-0.01 (-0.70)

[-0.03, 0.02]

-0.01 (-0.45)

[-0.03,0.02]

-0.02 (-096)

[-0.07,0.02]

-0.02 (-0.71)

[-0.06,0.03]

-0.02 (-0.88)

[-0.07,0.03]

-0.02 (-0.82)

[-0.06,0.03]

Firm size

-0.00 (-0.25)

[-0.03,0.02]

-0.00 (-0.28)

[-0.03,0.02]

-0.00 (-0.09)

[-0.04,0.04]

-0.00 (-0.05)

[-0.04,0.04]

-0.00 (-0.06)

[-0.04,0.04]

-0.00 (-0.02)

[-0.04,0.04]

Exploration

0.01 (0.97)

[-0.02,0.04]

0.02 (1.27)

[-0.01,0.05]

0.03 (1.07)

[-0.08,0.02]

-0.03 (-1.10)

[-0.09,0.03]

-0.03 (-1.19)

[-0.09,0.03]

-0.03 (-1.12)

[-0.09,0.03]

Exploitation

0.06 (4.38)***

[0.03, 0.08]

0.06 (4.29)***

[0.03, 0.08]

0.02 (.95)

[-0.02,0.07]

0.02 (0.72)

[-0.03,0.07]

0.01 (0.44)

[-0.04,0.06]

0.01 (0.58)

[-0.03,0.06]

Environmental dynamism

0.00 (0.08)

[-0.02,0.02]

0.00 (0.08)

[-0.02,0.02]

-0.02 (-0.77)

[-0.06,0.02]

-0.02 (-0.68)

[-0.06,0.03]

-0.02 (-0.78)

[-0.06,0.03]

-0.02 (-0.76)

[-0.06,0.03]

Absorptive capacity

-0.00 (-0.31)

[-0.03,0.02]

-0.00 (-0.32)

[-0.03,0.02]

0.04 (1.75)

[-0.00,0.08]

0.03 (1.53)

[-0.01,0.07]

0.04 (1.79)

[-0.00,0.08]

0.03 (1.70)

[-0.00,0.07]

Past performance

0.95 (4.02)***

[0.52, 1.50]

0.52 (1.66)

[-0.06, 1.10]

0.64 (1.47)

[-0.22,1.50]

0.64 (1.06)

[-0.45,2.03]

0.44 (1.00)

[-0.35,1.45]

0.47 (0.77)

[-0.62,1.76]

Direct effects

Alliance management capability

0.07 (3.04)**

[0.02, 0.12]

0.07 (2.84)**

[0.02, 0.11]

0.15 (3.49)***

[0.07,0.24]

0.14 (3.13)***

[0.05,0.22]

0.13 (2.84)**

[0.04,0.21]

Strategic flexibility

0.15 (2.76)**

0.08 (0.77)

[-0.14,0.28]

0.10 (0.94)

[-0.11,0.29]

Business model innovation

[0.04, 0.26]

0.23 (2.97)**

[0.06,0.39]

0.21 (2.72)**

[0.05,0.38]

0.20 (2.58)*

[0.03,0.37]

Interaction effects

Alliance management capability × Strategic flexibility

0.23 (2.58)**

[0.06, 0.40]

Business model innovation × Strategic flexibility

0.86 (3.19)**

[0.29,1.41]

0.77 (2.85)**

[0.20,1.31]

Regression model statistics

R2

0.11***

0.14***

0.04**

0.06***

0.05**

0.0**

Mediation analysis

Effect coefficient

Standard error

t-value

(X = Alliance management capability; Y= Eco-innovation performance; M = Business model innovation; 5,000 bootstraps):

Direct effect of X on Y

0.14***

[0.05,0.22]

0.04

3.13

Indirect effect of X on Y by M

0.02*

[0.002, 0.03]

Total effect of X on Y

0.15*

Direct effect of X on M

0.07**

[0.03, 0.12]

0.02

3.04

Standardized indirect effect b

0.01*

[0.002, 0.03]

Conclusion of R test

Mediation effect: Confirmed

Notes: We report unstandardized regression coefficients with t-values in parentheses. Values in square brackets represent bootstrapped 95% confidence interval values (unstandardized coefficients) [LL, UL].

* p < .05; ** p < 0.01; *** p < .001.

Table 12. Conditional effect of business model innovation and eco-innovation performance at values of the moderator (strategic flexibility)

Moderator: Strategic flexibility

Effect coefficient

t-value

95% CI [LL, UL]

-0.26

0.00

0.06

[-0.20, 0.21]

0.00

0.23**

2.97

[0.08, 0.39]

0.26

0.46***

4.33

[0.25, 0.67]

Notes: Values are -1 standard deviation, mean, +1 standard deviation.

* p < .05; ** p < 0.01; *** p < .001.

Table 13. Conditional indirect effect of firm alliance management capability on eco-innovation performance by business model innovation at values of the moderator (strategic flexibility)

Moderator: Strategic flexibility

Effect coefficient

t-value

95% CI [LL, UL]

-0.26

0.00

0.00

[-0.21, 0.21]

0.00

0.20*

2.58

[0.05, 0.36]

0.26

0.41***

3.79

[0.20, 0.62]

Notes: Values are -1 standard devi1ation, mean, +1 standard deviation.

* p < .05; ** p < 0.01; *** p < .001.

Table 13. Conditional indirect effect of firm alliance management capability on eco-innovation performance by business model innovation at values of the moderator (strategic flexibility)

Moderator: Strategic flexibility

Effect coefficient

t-value

95% CI [LL, UL]

-0.26

0.00

0.00

[-0.21, 0.21]

0.00

0.20*

2.58

[0.05, 0.36]

0.26

0.41***

3.79

[0.20, 0.62]

Notes: Values are -1 standard devi1ation, mean, +1 standard deviation.

* p < .05; ** p < 0.01; *** p < .001.

Table 14. Mediation analysis: SDG performance

Mediation analysis

Effect coefficient

Standard error

t-value

(X = Alliance management capability; Y= SDG performance; M = Strategic flexibility; 5,000 bootstraps):

Direct effect of X on Y

0.12***

[0.06, 0.17]

0.03

4.30

Indirect effect of X on Y by M

-0.00

[-0.01, 0.01]

0.00

0.09

Total effect of X on Y

0.12***

[0.06, 0.21]

0.03

4.21

Notes: Values in square brackets represent bootstrapped 95% confidence interval values (standardized coefficients) [LL, UL].

* p < .05; ** p < 0.01; *** p < .001.

Figure 2. The effect of alliance management capability on business model innovation at low and high levels of strategic flexibility

Figure 3. The effect of business model innovation on SDG performance at low and high levels of strategic flexibility

Table 4. Main analysis SEM results: SDG performance

Variables

Model 1

Business model innovation

Model 2

SDG performance

Model 3

Business model innovation

Model 4

SDG performance

Control and industry dummy variables

Manufacturing

0.00 (0.00)

[-0.09,0.09]

-0.04 (-0.84)

[-0.14,0.05]

-0.01 (-0.18)

[-0.10,0.09]

-0.04 (-0.91)

[-0.14,0.05]

Firm age

-0.04 (-0.77)

[-0.13,0.06]

-0.02 (-0.31)

[-0.11,0.09]

-0.04 (-0.88)

[-0.13,0.05]

-0.02 (-0.37)

[-0.11,0.08]

Firm size

-0.01 (-0.22)

[-0.09,0.08]

-0.01 (-0.16)

[-0.09,0.08]

-0.01 (-0.15)

[-0.09,0.08]

-0.01 (-0.13)

[-0.09,0.08]

Exploration

0.06 (1.13)

[-0.05,0.17]

-0.03 (-0.56)

[-0.14,0.08]

0.05 (0.87)

[-0.06,0.16]

-0.03 (-0.49)

[-0.13,0.09]

Exploitation

0.20 (4.19)***

[0.11, 0.30]

-0.02 (0.36)

[-0.12,0.08]

0.21 (4.25)***

[0.11, 0.30]

-0.01 (-0.21)

[-0.11,0.09]

Environmental dynamism

0.01 (0.11)

[-0.08,0.09]

-0.03 (-0.57)*

[-0.12,0.06]

0.00 (0.10)

[-0.08,0.09]

-0.02 (-0.48)

[-0.11,0.07]

Absorptive capacity

-0.01 (-0.28)

[-0.10,0.08]

0.09 (2.31)*

[0.13,0.16]

-0.01 (-0.28)

[-0.10,0.08]

0.08 (2.22)*

[0.01,0.16]

Past performance

0.09 (1.66)

[-0.01, 0.19]

-0.07 (-1.87)

[-0.00, 0.15]

0.16 (4.33)***

[0.09, 0.23]

0.05 (0.95)

[-0.05, 0.16]

Environmetal Volatity

-0.03 (-0.59)

[-0.11, 0.06]

-0.03 (-0.74)

[-0.12, 0.06]

-0.04 (-0.81)

[-0.12, 0.05]

-0.03 (-0.67)

[-0.12, 0.06]

Competitive Intensity

0.04 (0.97)

[-0.04, 0.11]

-0.05 (-0.98)

[-0.14, 0.05]

0.02 (0.56)

[-0.06, 0.10]

-0.03 (-0.65)

[-0.12, 0.06]

Direct effects

Alliance management capability

0.12 (2.78)**

[0.04, 0.20]

0.17 (3.84)***

[0.08,0.25]

0.13 (3.00)**

[0.05, 0.21]

0.15 (3.48)**

[0.07,0.24]

Strategic flexibility

0.15 (2.78)**

[0.04, 0.25]

0.12 (1.99)

[-0.01,0.20]

Business model innovation

0.15 (3.26)*

[0.06,0.24]

0.14 (3.02)**

[0.05,0.23]

Interaction effects

Alliance management capability × Strategic flexibility

0.11 (2.59)*

[0.02, 0.19]

Business model innovation × Strategic flexibility

0.15 (3.38)**

[0.06,0.24]

Residual Variances

0.88 (31.50)***

[0.84, 0.94]

0.95 (55.91)***

[0.94, 0.98]

0.89 (33.27)***

[0.91, 0.98]

0.91 (35.96)***

[0.91, 0.98]

R2

0.13***

0.05**

0.11***

0.09***

Mediation analysis

Effect coefficient

Standard error

t-value

(X = Alliance management capability; Y= SDG performance; M = Business model innovation; 5,000 bootstraps):

Direct effect of X on Y

0.11***

[0.05, 0.16]

0.03

3.89

Indirect effect of X on Y by M

0.01*

[0.00, 0.03]

0.02

2.12

Total effect of X on Y

0.12*

[0.06, 0.17]

0.03

4.29

Notes: Values in square brackets represent bootstrapped 95% confidence interval values (standardized coefficients) [LL, UL].

* p < .05; ** p < 0.01; *** p < .001.

Table 5. Conditional effect of alliance management capability and business model innovation at values of the moderator (strategic flexibility)

path

Mo

First stage

(X→ME)

Second stage

(ME→Y)

Indirect effect ( X→ME→Y)

Total effect

Alliance management capability Business model innovation SDG performance

high strategic flexibility

0.13[0.07, 0.18]

0.17[0.03, 0.28]

0.11[0.01, 0.04]

0.13[0.07, 0.18]

low strategic flexibility

0.01[-0.07, 0.08]

0.17[ 0.07, 0.28]

0.11[-0.01, 0.02]

0.11[0.05, 0.16]

difference

0.12[ 0.03, 0.21]

0.02[0.00, 0.05]

0.02[0.00, 0.05]

Index of moderated mediation

0.05[0.01, 0.09]

Notes: Values are -1 standard deviation, mean, +1 standard deviation.

* p < .05; ** p < 0.01; *** p < .001.

Table 6. Conditional effect of business model innovation and SDG performance at values of the moderator (strategic flexibility)

path

Mo

First stage

(X→ME)

Second stage

(ME→Y)

Indirect effect ( X→ME→Y)

Total effect

Alliance management capability → Business model innovation → SDG performance

high strategic flexibility

0.07[0.03, 0.12]

0.31[0.16, 0.46]

0.10[0.01, 0.04]

0.12[0.06, 0.17]

low strategic flexibility

0.07[0.03,0.12]

0.01[-0.11, 0.12]

0.00[-0.01, 0.01]

0.10[0.04, 0.15]

difference

0.31[ 0.13, 0.48]

0.02[0.01, 0.05]

0.02[0.00, 0.05]

Index of moderated mediation

0.04[ .01, .09]

Notes: Values are -1 standard deviation, mean, +1 standard deviation.

* p < .05; ** p < 0.01; *** p < .001.

Table 6. Post-hoc analysis SEM results: Social innovation performance

Variables

Model 1

Business model innovation

Model 2

Social innovation performance

Model 3

Business model innovation

Model 4

Social innovation performance

Control and industry dummy variables

Manufacturing

0.00 (0.00)

[-0.09,0.09]

0.02 (0.37)

[-0.07,0.10]

-0.01 (-0.18)

[-0.10,0.09]

0.02 (0.39)

[-0.07,0.10]

Firm age

-0.04 (-0.77)

[-0.13,0.06]

0.02 (0.38)

[-0.08,0.12]

-0.04 (-0.88)

[-0.13,0.05]

0.02 (0.36)

[-0.08,0.12]

Firm size

-0.01 (-0.22)

[-0.09,0.08]

-0.01 (-0.32)

[-0.10,0.07]

-0.01 (-0.15)

[-0.09,0.08]

-0.01 (-0.31)

[-0.10,0.07]

Exploration

0.06 (1.13)

[-0.05,0.17]

0.03 (0.65)

[-0.07,0.13]

0.05 (0.87)

[-0.06,0.16]

0.04 (0.75)

[-0.06,0.13]

Exploitation

0.20 (4.19)***

[0.11, 0.30]

-0.08 (-1.47)

[-0.18,0.03]

0.21 (4.25)***

[0.11, 0.30]

-0.07 (-1.40)

[-0.17,0.03]

Environmental dynamism

0.01 (0.11)

[-0.08,0.09]

0.01 (0.11)

[-0.08,0.09]

0.00 (0.10)

[-0.08,0.09]

0.01 (0.25)

[-0.08,0.10]

Absorptive capacity

-0.01 (-0.28)

[-0.10,0.08]

0.06 (1.40)

[-0.03,0.14]

-0.01 (-0.28)

[-0.10,0.08]

0.06 (1.31)

[-0.03,0.14]

Past performance

0.09 (1.66)

[-0.01, 0.19]

0.08 (2.36)*

[0.01, 0.14]

0.16 (4.33)***

[0.09, 0.23]

0.03 (0.61)

[-0.07, 0.14]

Environmetal Volatity

-0.03 (-0.59)

[-0.11, 0.06]

-0.06 (-1.11)

[-0.13, 0.04]

-0.04 (-0.81)

[-0.12, 0.05]

-0.04 (-1.02)

[-0.15, 0.05]

Competitive Intensity

0.04 (0.97)

[-0.04, 0.11]

-0.06 (-1.19)

[-0.15, 0.04]

0.02 (0.56)

[-0.06, 0.10]

-0.04 (-0.88)

[-0.13, 0.05]

Direct effects

Alliance management capability

0.12 (2.78)**

[0.04, 0.20]

0.25 (2.87)**

[0.04,0.20]

0.13 (3.00)**

[0.05, 0.21]

0.09 (2.63)**

[0.06,0.41]

Strategic flexibility

0.15 (2.78)**

[0.04, 0.23]

0.12 (2.33) *

[0.02,0.22]

Business model innovation

0.12 (2.73)*

[0.03,0.19]

0.11 (2.45)*

[0.02,0.22]

Interaction effects

Alliance management capability × Strategic flexibility

0.11 (2.59)*

[0.02, 0.19]

Business model innovation × Strategic flexibility

0.11 (2.72)**

[0.37,2.25]

Residual Variances

0.88 (31.50)***

[0.84, 0.94]

0.95 (55.91)***

[0.94, 0.98]

0.89 (33.27)***

[0.85, 0.94]

0.94 (48.41)***

[0.93, 0.97]

R2

0.13***

0.05**

0.11***

0.06**

Mediation analysis

Effect coefficient

Standard error

t-value

(X = Alliance management capability; Y= Social innovation performance ; performance; M = Business model innovation; 5,000 bootstraps):

Direct effect of X on Y

0.08**

[0.04, 0.20]

0.03

2.86

Indirect effect of X on Y by M

0.01*

[0.00, 0.03]

0.02

2.00

Total effect of X on Y

0.08**

[0.05, 0.21]

0.03

3.22

Notes: We report unstandardized regression coefficients with t-values in parentheses. Values in square brackets represent bootstrapped 95% confidence interval values (unstandardized coefficients) [LL, UL].

* p < .05; ** p < 0.01; *** p < .001.

Table 7. Conditional effect of business model innovation and social innovation performance at values of the moderator (strategic flexibility)

path

Mo

First stage

(X→ME)

Second stage

(ME→Y)

Indirect effect ( X→ME→Y)

Total effect

Alliance management capability → Business model innovation → SDG performance

high strategic flexibility

0.13[0.07, 0.18]

0.13[0.04, 0.22]

0.02[0.01, 0.03]

0.09[0.04, 0.14]

low strategic flexibility

0.01[-0.07, 0.08]

0.13[ 0.04, 0.22]

0.00[-0.01, 0.01]

0.08[0.02, 0.13]

difference

0.12[ 0.03, 0.21]

0.02[0.00, 0.04]

0.02[0.00, 0.04]

Index of moderated mediation

0.05[0.01, 0.07]

Notes: Values are -1 standard deviation, mean, +1 standard deviation.

* p < .05; ** p < 0.01; *** p < .001.

Table 8. Conditional indirect effect of alliance management capability on social innovation performance by business model innovation at values of the moderator (strategic flexibility)

path

Mo

First stage

(X→ME)

Second stage

(ME→Y)

Indirect effect ( X→ME→Y)

Total effect

Alliance management capability → Business model innovation → SDG performance

high strategic flexibility

0.07[0.03, 0.12]

0.22[0.10, 0.34]

0.02[0.01, 0.03]

0.09[0.03, 0.14]

low strategic flexibility

0.07[0.03,0.12]

0.01[-0.10, 0.12]

0.00[-0.01, 0.01]

0.07[0.02, 0.12]

difference

0.21[ 0.06, 0.35]

0.02[0.00, 0.04]

0.02[0.00, 0.04]

Index of moderated mediation

0.04[ .01, .07]

Notes: Values are -1 standard deviation, mean, +1 standard deviation.

* p < .05; ** p < 0.01; *** p < .001.

Table 9. Post-hoc analysis SEM results: Eco-innovation performance

Variables

Model 1

Business model innovation

Model 2

Eco-innovation performance

Model 3

Business model innovation

Model 4

Eco-innovation performance

Control and industry dummy variables

Manufacturing

0.00 (0.00)

[-0.09,0.09]

-0.06 (-1.22)

[-0.16,0.04]

-0.01 (-0.18)

[-0.10,0.09]

-0.07(-1.30)

[-0.16,0.03]

Firm age

-0.04 (-0.77)

[-0.13,0.06]

-0.03 (-0.61)

[-0.13,0.07]

-0.04 (-0.88)

[-0.13,0.05]

-0.03(-0.67)

[-0.13,0.06]

Firm size

-0.01 (-0.22)

[-0.09,0.08]

0.00 (-0.00)

[-0.09,0.08]

-0.01 (-0.15)

[-0.09,0.08]

0.00(0.02)

[-0.08,0.08]

Exploration

0.06 (1.13)

[-0.05,0.17]

-0.06 (-1.00)

[-0.18,0.06]

0.05 (0.87)

[-0.06,0.16]

-0.06(-0.96)

[-0.17,0.06]

Exploitation

0.20 (4.19)***

[0.11, 0.30]

0.02 (0.44)

[-0.08,0.12]

0.21 (4.25)***

[0.11, 0.30]

0.03(0.58)

[-0.07,0.13]

Environmental dynamism

0.01 (0.11)

[-0.08,0.09]

-0.04 (-0.75)

[-0.13,0.06]

0.00 (0.10)

[-0.08,0.09]

-0.04(-0.73)

[-0.13,0.06]

Absorptive capacity

-0.01 (-0.28)

[-0.10,0.08]

0.08 (1.83)

[-0.01,0.16]

-0.01 (-0.28)

[-0.10,0.08]

0.07(1.76)

[0.01,0.15]

Past performance

0.09 (1.66)

[-0.01, 0.19]

0.04 (1.06)

[-0.03, 0.13]

0.16 (4.33)***

[0.09, 0.23]

0.05 (0.82)

[-0.07, 0.16]

Environmetal Volatity

-0.03 (-0.59)

[-0.11, 0.06]

-0.01 (-0.31)

[-0.10, 0.08]

-0.04 (-0.81)

[-0.12, 0.05]

-0.01(-0.28)

[-0.10, 0.08]

Competitive Intensity

0.04 (0.97)

[-0.04, 0.11]

-0.03 (-0.56)

[-0.12, 0.07]

0.02 (0.56)

[-0.06, 0.10]

-0.01(-0.30)

[-0.11, 0.08]

Direct effects

Alliance management capability

0.12 (2.78)**

[0.04, 0.20]

0.14 (3.19)**

[0.06,0.22]

0.13 (3.00)**

[0.05, 0.21]

0.12(2.83)**

[0.04,0.21]

Strategic flexibility

0.15 (2.78)**

[0.04, 0.25]

0.05(0.89)

[-0.06,0.16]

Business model innovation

0.12 (2.53)*

[0.03,0.21]

0.12(2.37)*

[0.02,0.21]

Interaction effects

Alliance management capability × Strategic flexibility

0.11 (2.59)*

[0.02, 0.19]

Business model innovation × Strategic flexibility

0.13(2.62)**

[0.03,0.22]

Residual Variances

0.88 (31.50)***

[0.84, 0.94]

0.95 (47.49)***

[0.93, 0.98]

0.89 (33.27)***

[0.91, 0.98]

0.94(40.15)***

[0.92, 0.98]

R2

0.13***

0.05*

0.11***

0.06**

Mediation analysis

Effect coefficient

Standard error

t-value

(X = Alliance management capability; Y= Eco-innovation performance; M = Business model innovation; 5,000 bootstraps):

Direct effect of X on Y

0.14**

[0.04, 0.21]

0.04

3.20

Indirect effect of X on Y by M

0.01*

[0.00, 0.04]

0.01

1.99

Total effect of X on Y

0.15***

[0.06, 0.22]

0.04

3.55

Notes: We report unstandardized regression coefficients with t-values in parentheses. Values in square brackets represent bootstrapped 95% confidence interval values (unstandardized coefficients) [LL, UL].

* p < .05; ** p < 0.01; *** p < .001.

Table 10. Conditional effect of business model innovation and eco-innovation performance at values of the moderator (strategic flexibility)

path

Mo

First stage

(X→ME)

Second stage

(ME→Y)

Indirect effect ( X→ME→Y)

Total effect

Alliance management capability → Business model innovation → eco-innovation performance

high strategic flexibility

0.13[0.07, 0.18]

0.21[0.06, 0.39]

0.03[0.01, 0.06]

0.17[0.08, 0.25]

low strategic flexibility

0.01[-0.07, 0.08]

0.21[ 0.07, 0.39]

0.00[-0.02, 0.02]

0.14[0.06, 0.23]

difference

0.12[ 0.03, 0.21]

0.04[0.01, 0.07]

0.04[0.01, 0.07]

Index of moderated mediation

0.05[0.01, 0.13]

Notes: Values are -1 standard deviation, mean, +1 standard deviation.

* p < .05; ** p < 0.01; *** p < .001.

Table 11. Conditional indirect effect of firm alliance management capability on eco-innovation performance by business model innovation at values of the moderator (strategic flexibility)

path

Mo

First stage

(X→ME)

Second stage

(ME→Y)

Indirect effect ( X→ME→Y)

Total effect

Alliance management capability → Business model innovation → eco-innovation performance

high strategic flexibility

0.07[0.03, 0.12]

0.41[0.16, 0.66]

0.03[0.01, 0.06]

0.16[0.07, 0.24]

low strategic flexibility

0.07[0.03,0.12]

0.00[-0.21, 0.20]

0.00[-0.02, 0.02]

0.13[0.04, 0.21]

difference

0.41[ 0.10, 0.71]

0.03[0.01, 0.07]

0.03[0.01, 0.07]

Index of moderated mediation

0.07[ .01, .13]

Notes: Values are -1 standard devi1ation, mean, +1 standard deviation.

* p < .05; ** p < 0.01; *** p < .001.

Table 12. Conditional effect of business model innovation and eco-innovation performance at values of the moderator (strategic flexibility)

Moderator: Strategic flexibility

Effect coefficient

t-value

95% CI [LL, UL]

-0.26

0.00

0.06

[-0.20, 0.21]

0.00

0.23**

2.97

[0.08, 0.39]

0.26

0.46***

4.33

[0.25, 0.67]

Notes: Values are -1 standard deviation, mean, +1 standard deviation.

* p < .05; ** p < 0.01; *** p < .001.

Table 13. Conditional indirect effect of firm alliance management capability on eco-innovation performance by business model innovation at values of the moderator (strategic flexibility)

Moderator: Strategic flexibility

Effect coefficient

t-value

95% CI [LL, UL]

-0.26

0.00

0.00

[-0.21, 0.21]

0.00

0.20*

2.58

[0.05, 0.36]

0.26

0.41***

3.79

[0.20, 0.62]

Notes: Values are -1 standard devi1ation, mean, +1 standard deviation.

* p < .05; ** p < 0.01; *** p < .001.

Table 14. Mediation analysis: SDG performance

Mediation analysis

Effect coefficient

Standard error

t-value

(X = Alliance management capability; Y= SDG performance; M = Strategic flexibility; 5,000 bootstraps):

Direct effect of X on Y

0.12***

[0.06, 0.17]

0.03

4.30

Indirect effect of X on Y by M

-0.00

[-0.01, 0.01]

0.00

0.09

Total effect of X on Y

0.12***

[0.06, 0.21]

0.03

4.21

Notes: Values in square brackets represent bootstrapped 95% confidence interval values (standardized coefficients) [LL, UL].

* p < .05; ** p < 0.01; *** p < .001.

Appendix. Survey items

Alliance management capability (Schilke and Goerzen, 2010)

Interorganizational coordination

Our activities with external relationships/alliance partners are well coordinated.

We ensure that our work is synchronized with the work of our external relationships/alliance partners.

There is a great deal of interaction with our external relationships/alliances partners on most decisions.

Alliance portfolio coordination

We ensure an appropriate coordination among the activities of our external relationships/different alliances.

We determine areas of synergy in our external relationships/alliance portfolio.

We ensure that interdependencies between our external relationships/alliance are identified.

We determine if there are overlaps between our external relationships/different alliances.

Interorganizational learning

We have the capability to learn from our external relationship/alliance partners.

We have the managerial competence to absorb new knowledge from our external relationships/alliance partners.

We have adequate routines to analyze the information obtained from our external relationships/alliance partners.

We can successfully integrate our existing knowledge with new information acquired from external relationships and our alliance partners.

Alliance proactiveness

We strive to preempt our competition by entering into firm opportunities with our external relationships/alliance partners.

We often take the initiative in approaching external relationships/alliance partners with our firm proposals.

Compared to our competitors, we are far more proactive and responsive in finding and going after external relationships/alliance partnerships.

We actively monitor our environment to identify external relationships/alliance partnership opportunities.

Alliance transformation

We are willing to put aside contractual terms with external relationships/alliances to improve the outcome of our firms.

When an unexpected situation arises, we would rather modify a firm agreement by using external relationships/alliances than insist on the original terms.

Flexibility, in response to a request for change, is characteristic of our firm management process with external relationship/alliances.

Business model innovation (Von Delft et al., 2019)

Over the last five years we have significantly changed …

… our target customers and/or customer segments.

… our way of satisfying important customer needs.

… our product/service offering.

… the design of our product/service offering.

… the price of our product/service offering.

… our pricing and sales strategy.

… our commercialization strategy (e.g., subscription fees, leasing, licensing).

… the cost structure of our product/service offering.

… the calculation of strategically important costs.

… our manufacturing/operations strategy (e.g., operational excellence projects).

… the cost structure of our operational processes.

… our key performance indicators (e.g., ROI, ROA, inventory turns, or lead times).

Strategic flexibility (Grewal and Tansuhaj, 2001)

We regularly share costs across business activities.

We frequently change our strategies and structures to derive benefits from environmental (political, economic, and financial) changes.

Our strategy emphasizes exploiting new opportunities arising from environmental changes.

Our strategy reflects a high level of flexibility in managing political, economic, and financial risks.

Our strategy emphasizes versatility and empowerment in allocating human resources.

Innovation strategy (Jansen et al., 2006)

Exploration

Our firm accepts demands that go beyond existing products and services.

We invent new products and services.

We experiment with new products and services in our local market.

We commercialize products and services that are completely new to our firm.

We frequently utilize new opportunities in new markets.

Our firm regularly uses new distribution channels.

We regularly search for and approach new clients in new markets.

Exploitation

We frequently refine the provision of existing products and services.

We regularly implement small adaptations to existing products and services.

We introduce improved, but existing products and services for our local market.

We improve our provisions efficiency of products and services.

We increase economies of scales in existing markets.

Our firm expands services for existing clients.

Lowering costs of internal processes is an important objective.

Absorptive capacity (Jansen et al., 2005)

Our firm has frequent interactions with corporate headquarters to acquire new knowledge.

Employees of our firm regularly visit other branches.

We collect industry information through informal means (e.g. lunch with industry friends, talks with trade partners).

Other divisions of our company are hardly visited.

Our firm periodically organizes special meetings with customers or third parties to acquire new knowledge.

Employees regularly approach third parties such as accountants, consultants, or tax consultants.

We are slow to recognize shifts in our market (e.g. competition, regulation, demography).

New opportunities to serve our clients are quickly understood.

We quickly analyze and interpret changing market demands.

Our firm regularly considers the consequences of changing market demands in terms of new products and services.

Employees record and store newly acquired knowledge for future reference.

Our firm quickly recognizes the usefulness of new external knowledge to existing knowledge.

Employees hardly share practical experiences.

We laboriously grasp the opportunities for our firm from new external knowledge.

Our firm periodically meets to discuss consequences of market trends and new product development.

It is clearly known how activities within our firm should be performed.

Client complaints fall on deaf ears in our firm.

Our firm has a clear division of roles and responsibilities.

We constantly consider how to better exploit knowledge.

Our firm has difficulty implementing new products and services.

Employees have a common language regarding our products and services.

Environmental dynamism (Jansen et al., 2006)

Environmental changes in our local market are intense.

Our clients regularly ask for new products and services.

In our local market, changes are taking place continuously.

In a year, nothing has changed in our market.

In our market, the volumes of products and services to be delivered change fast and often.

Social-innovation performance (Gutierrez et al., 2022)

1. Improving employee health and safety.

2. Increasing total employment.

3. Increasing qualified employment.

4. Maintaining existing employment.

5. Compliance with health and safety regulations.

Eco-innovation performance (Gutierrez et al., 2022)

1. Reducing environmental impact.

2. Lower energy consumed per unit.

3. Lower materials employed per unit.

4. Higher production or service provision flexibility.

5. Higher production or service provision capacity.

Appendix Table 1. CMV results: SDG performance

Variables

Model 1

Business model innovation

Model 2

SDG performance

Model 3

Business model innovation

Model 4

SDG performance

Control and industry dummy variables

Manufacturing

0.00 (0.04)

[-0.09,0.09]

-0.02 (-0.36)

[-0.10,0.07]

-0.01 (-0.14)

[-0.09,0.09]

-0.01 (-0.34)

[-0.10,0.07]

Firm age

-0.04 (-0.78)

[-0.13,0.06]

-0.02 (-0.52)

[-0.11,0.06]

-0.04 (-0.89)

[-0.13,0.05]

-0.02 (-0.56)

[-0.11,0.06]

Firm size

-0.01 (-0.27)

[-0.10,0.08]

-0.04 (-1.07)

[-0.12,0.03]

-0.01 (-0.21)

[-0.10,0.08]

-0.04 (-1.08)

[-0.11,0.03]

Exploration

0.06 (1.14)

[-0.05,0.17]

-0.02 (-0.41)

[-0.11,0.07]

0.05 (0.89)

[-0.06,0.16]

-0.02 (-0.33)

[-0.10,0.08]

Exploitation

0.20 (4.15)***

[0.10, 0.30]

-0.03 (0.75)

[-0.12,0.05]

0.21 (4.22)***

[0.10, 0.30]

-0.03 (-0.64)

[-0.11,0.06]

Environmental dynamism

0.01 (0.11)

[-0.08,0.09]

-0.03 (-0.80)

[-0.11,0.04]

0.00 (0.09)

[-0.08,0.09]

-0.03 (-0.62)

[-0.10,0.05]

Absorptive capacity

-0.01 (-0.30)

[-0.10,0.08]

0.07 (2.10)*

[0.00,0.13]

-0.01 (-0.30)

[-0.10,0.07]

0.07 (2.00)*

[0.00,0.13]

Past performance

0.08 (1.58)

[-0.02, 0.19]

0.04 (1.23)

[-0.02, 0.11]

0.16 (4.23)***

[0.09, 0.23]

-0.02 (-0.39)

[-0.10, 0.07]

Environmetal Volatity

-0.03 (-0.60)

[-0.11, 0.06]

-0.04 (-1.03)

[-0.11, 0.04]

-0.04 (-0.82)

[-0.12, 0.05]

-0.03 (-0.90)

[-0.10, 0.04]

Competitive Intensity

0.04 (0.97)

[-0.04, 0.11]

-0.05 (-1.19)

[-0.13, 0.03]

0.02 (0.56)

[-0.06, 0.10]

-0.03 (-0.78)

[-0.11, 0.05]

Work life balance

0.03 (0.81)

[-0.05, 0.11]

0.52 (15.55)***

[0.45, 0.58]

0.04 (0.84)

[-0.05, 0.12]

0.52 (15.51)***

[0.45, 0.58]

Direct effects

Alliance management capability

0.11(2.70)**

[0.03, 0.19]

0.12 (3.43)**

[0.05,0.19]

0.12 (2.93)**

[0.04, 0.20]

0.11 (3.16)**

[0.04,0.18]

Strategic flexibility

0.15 (2.83)**

[0.04, 0.25]

0.14 (3.02)**

[0.05,0.23]

Business model innovation

0.13 (3.28)**

[0.05,0.21]

0.12 (2.90)**

[0.04,0.20]

Interaction effects

Alliance management capability × Strategic flexibility

0.10(2.53)*

[0.02, 0.19]

Business model innovation × Strategic flexibility

0.11 (2.99)**

[0.04,0.18]

Residual Variances

0.87(31.48)***

[0.84, 0.94]

0.67(19.50)***

[0.62, 0.74]

0.89 (33.28)***

[0.85, 0.94]

0.65 (18.99)***

[0.60, 0.72]

R2

0.13***

0.33**

0.12***

0.35***

Mediation analysis

Effect coefficient

Standard error

t-value

(X = Alliance management capability; Y= SDG performance; M = Business model innovation; 5,000 bootstraps):

Direct effect of X on Y

0.12**

[0.05, 0.19]

0.04

3.43

Indirect effect of X on Y by M

0.02*

[0.00, 0.03]

0.01

2.09

Total effect of X on Y

0.14***

[0.06, 0.21]

0.04

3.78

Notes: Values in square brackets represent bootstrapped 95% confidence interval values (standardized coefficients) [LL, UL].

* p < .05; ** p < 0.01; *** p < .001.

Appendix Table 2. CMV results: Social innovation performance

Variables

Model 1

Business model innovation

Model 2

Social innovation performance

Model 3

Business model innovation

Model 4

Social innovation performance

Control and industry dummy variables

Manufacturing

0.00 (0.04)

[-0.02,0.03]

0.02 (0.49)

[-0.02,0.03]

-0.01 (-0.14)

[-0.09,0.09]

0.02 (0.53)

[-0.07,0.11]

Firm age

-0.04 (-0.78)

[-0.04,0.02]

0.02 (0.35)

[-0.02,0.03]

-0.04 (-0.89)

[-0.13,0.05]

0.02 (0.34)

[-0.08,0.11]

Firm size

-0.01 (-0.27)

[-0.03,0.02]

-0.02 (-0.48)

[-0.03,0.02]

-0.01 (-0.21)

[-0.10,0.08]

-0.02(-0.48)

[-0.11,0.07]

Exploration

0.06 (1.14)

[-0.01,0.05]

0.04(0.72)

[-0.02,0.04]

0.05 (0.89)

[-0.06,0.16]

0.04 (0.82)

[-0.06,0.13]

Exploitation

0.20 (4.15)***

[0.03, 0.08]

-0.08 (-1.56)

[-0.05,0.01]

0.21 (4.22)***

[0.10, 0.30]

-0.08(-1.49)

[-0.17,0.03]

Environmental dynamism

0.01 (0.11)

[-0.02,0.03]

0.00 (0.08)

[-0.02,0.03]

0.00 (0.09)

[-0.08,0.09]

0.01 (0.24)

[-0.08,0.10]

Absorptive capacity

-0.01 (-0.30)

[-0.03,0.02]

0.06 (1.31)

[-0.01,0.04]

-0.01 (-0.30)

[-0.10,0.07]

0.05(1.22)

[-0.04,0.13]

Past performance

0.08(1.58)

[-0.01, 0.05]

0.07(2.27)*

[0.00, 0.04]

0.16 (4.23)***

[0.09, 0.23]

0.02(0.34)

[-0.07, 0.12]

Environmetal Volatity

-0.03 (-0.60)

[-0.04, 0.02]

-0.05(-1.16)

[-0.05, 0.01]

-0.04 (-0.82)

[-0.12, 0.05]

-0.04 (-1.06)

[-0.12, 0.04]

Competitive Intensity

0.04 (0.97)

[-0.01, 0.03]

-0.06 (-1.21)

[-0.05, 0.01]

0.02 (0.56)

[-0.06, 0.10]

-0.04 (-0.89)

[-0.13, 0.05]

Work life balance

0.03(0.81)

[-0.01, 0.03]

0.12(2.65)**

[0.01, 0.06]

0.04 (0.84)

[-0.05, 0.12]

0.11(2.64)**

[0.03, 0.20]

Direct effects

Alliance management capability

0.11(2.70)**

[0.02, 0.11]

0.11(2.62)**

[0.02,0.12]

0.12(2.93)**

[0.04, 0.20]

0.10(2.43)*

[0.02,0.18]

Strategic flexibility

0.15 (2.83)**

[0.04, 0.27]

0.13(2.56) *

[0.03,0.22]

Business model innovation

0.11(2.63)**

[0.03,0.22]

0.10(2.34)*

[0.02,0.18]

Interaction effects

Alliance management capability × Strategic flexibility

0.10(2.53)*

[0.05, 0.40]

Business model innovation × Strategic flexibility

0.10(2.53)**

[0.37,2.25]

Residual Variances

0.87(31.48)***

[0.06, 0.07]

0.93(48.41)***

[0.08, 0.10]

0.89 (33.28)***

[0.85, 0.94]

0.93(43.88)***

[0.91, 0.96]

R2

0.13***

0.06**

0.12***

0.08***

Mediation analysis

Effect coefficient

Standard error

t-value

(X = Alliance management capability; Y= Social innovation performance ; performance; M = Business model innovation; 5,000 bootstraps):

Direct effect of X on Y

0.11**

[0.03, 0.20]

0.04

2.62

Indirect effect of X on Y by M

0.02*

[0.00, 0.03]

0.02

2.01

Total effect of X on Y

0.12**

[0.04, 0.20]

0.04

2.96

Notes: Values in square brackets represent bootstrapped 95% confidence interval values (standardized coefficients) [LL, UL].

* p < .05; ** p < 0.01; *** p < .001.

Appendix Table 3. CMV results: Eco innovation performance

Variables

Model 1

Business model innovation

Model 2

Eco-innovation performance

Model 3

Business model innovation

Model 4

Eco-innovation performance

Control and industry dummy variables

Manufacturing

0.00 (0.04)

[-0.09,0.09]

-0.03(-.79)

[-0.11,0.05]

-0.01 (-0.14)

[-0.03,0.02]

-0.03(-0.77)

[-0.06,0.02]

Firm age

-0.04 (-0.78)

[-0.13,0.06]

-0.04(-0.97)

[-0.12,0.04]

-0.04 (-0.89)

[-0.04,0.02]

-0.04(-1.00)

[-0.06,0.02]

Firm size

-0.01 (-0.27)

[-0.10,0.08]

0.04(-1.10)

[-0.11,0.03]

-0.01 (-0.21)

[-0.03,0.02]

-0.04(-1.10)

[-0.05,0.02]

Exploration

0.06 (1.14)

[-0.05,0.17]

-0.05(-0.92)

[-0.14,0.06]

0.05(0.89)

[-0.02,0.04]

-0.04(-0.86)

[-0.07,0.03]

Exploitation

0.20 (4.15)***

[0.10, 0.30]

0.01(0.16)

[-0.08,0.09]

0.21(4.22)***

[0.03, 0.08]

0.01(0.26)

[-0.03,0.05]

Environmental dynamism

0.01 (0.11)

[-0.08,0.09]

-0.04 (-1.04)

[-0.13,0.04]

0.00 (0.09)

[-0.02,0.02]

-0.04(-0.93)

[-0.06,0.02]

Absorptive capacity

-0.01 (-0.30)

[-0.10,0.08]

0.05(1.54)

[-0.02,0.12]

-0.01 (-0.30)

[-0.03,0.02]

0.05(1.48)

[-0.01,0.06]

Past performance

0.08(1.58)

[-0.02, 0.19]

0.01(0.19)

[-0.07, 0.09]

0.16 (4.23)***

[0.02, 0.07]

-0.03 (-0.60)

[-0.06, 0.04]

Environmetal Volatity

-0.03 (-0.60)

[-0.11, 0.06]

-0.02(-0.55)

[-0.09, 0.05]

-0.04 (-0.82)

[-0.04, 0.02]

-0.02(-0.45)

[-0.05, 0.03]

Competitive Intensity

0.04 (0.97)

[-0.04, 0.11]

-0.03 (-0.74)

[-0.10, 0.04]

0.02 (0.56)

[-0.02, 0.03]

-0.02(-0.39)

[-0.05, 0.03]

Work life balance

0.03(0.81)

[-0.05, 0.11]

0.59(20.32)***

[-0.53, 0.64]

0.04 (0.84)

[-0.01, 0.03]

0.58 (20.02)***

[0.25, 0.32]

Direct effects

Alliance management capability

0.11(2.70)**

[0.03, 0.19]

0.09(2.70)**

[0.02,0.15]

0.12(2.93)**

[0.03, 0.12]

0.08(2.44)**

[0.02,0.15]

Strategic flexibility

0.15 (2.83)**

[0.04, 0.25]

0.10(2.05)*

[0.01,0.34]

Business model innovation

0.10(2.52)*

[0.02,0.17]

0.09(2.20)*

[0.02,0.29]

Interaction effects

Alliance management capability × Strategic flexibility

0.10(2.53)*

[0.02, 0.19]

Business model innovation × Strategic flexibility

0.08(2.03)*

[0.02,0.97]

Residual Variances

0.87(31.47)***

[0.84, 0.94]

0.61(18.72)***

[0.57, 0.69]

0.89 (33.28)***

[0.06, 0.08]

0.60(18.81)***

[0.12, 0.17]

R2

0.13***

0.39*

0.12***

0.40**

Mediation analysis

Effect coefficient

Standard error

t-value

(X = Alliance management capability; Y= Eco-innovation performance; M = Business model innovation; 5,000 bootstraps):

Direct effect of X on Y

0.09**

[0.02, 0.15]

0.03

2.70

Indirect effect of X on Y by M

0.01*

[0.00, 0.03]

0.02

2.01

Total effect of X on Y

0.10**

[0.04, 0.16]

0.03

3.02

Notes: Values in square brackets represent bootstrapped 95% confidence interval values (standardized coefficients) [LL, UL].

* p < .05; ** p < 0.01; *** p < .001.

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