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PurposeThe purpose of this paper is to examine when and how organizations build big data analytics capability (BDAC) to improve supply chain agility (SCA) and gain competitive advantage.Design/methodology/approachThe authors grounded the theoretical framework in two perspectives: the dynamic capabilities view and contingency theory. To test the research hypotheses, the authors gathered 173 usable responses using a pre-tested questionnaire.FindingsThe results suggest that BDAC has a positive and significant effect on SCA and competitive advantage. Further, the results support the hypothesis that organizational flexibility (OF) has a positive and significant moderation effect on the path joining BDAC and SCA. However, contrary to the belief, the authors found no support for the moderation effect of OF on the path joining BDAC and competitive advantage.Originality/valueThe study makes some useful contributions to the literature on BDAC, SCA, OF, and competitive advantage. Moreover, the results may further motivate future scholars to replicate the findings using longitudinal data.

PurposeWith considerable international awareness of circular economy (CE), the purpose of this paper is to propose a theoretical framework, informed by institutional theory and upper echelon theory (UET), to explain how top management commitment (TMC) mediates the relationship between external pressures and supplier relationship management (SRM) practices for CE.Design/methodology/approachThe authors test the hypotheses using cross-sectional data gathered using a survey of companies involved in sustainability practices.FindingsThe results of the hierarchical regression and mediating regression analyses suggest that TMC positively mediates the effect of external institutional pressures on SRM.Originality/valueThe authors advance existing theory by integrating institutional theory and UET to explain SRM practices in sustainable supply networks. Furthermore, the authors offer guidance to managers who would like to engage in leveraging SRM in sustainable supply networks and outline future research directions.

In recent years, there has been a proliferation of interest in resilience in the supply chain field. Even though literature has acknowledged the antecedents of resilient supply chains, such as supply chain visibility, cooperation, and information sharing, their confluence in creating resilient supply chains where other behavioural issues are prevailing (i.e. trust and behavioural uncertainty) has not been studied. To address this gap, we conceptualized a theoretical framework firmly grounded in the resource based view (RBV) and the relational view that is tested for 250 manufacturing firms using hierarchical moderated regression analysis. The study offers a nuanced understanding of supply chain resilience and implications of supply chain visibility, cooperation, trust and behavioural uncertainty. Implications and suggestions for further research are provided.

This paper is a review of the current literature on modelling industrial processes and integrating automation along with the digitisation drive of Industry 4.0 with the purpose of identifying promising directions for future research. Future research will involve working with an automation integration company to develop and test a methodology for assessing manufacturing enterprises to identify areas or processes that can economically be made more efficient through robotics and automation. The expected outcome of the research will be a system that streamlines and speeds up automating and digitalising the manufacturing industry.

This study examines the effects of supply chain agility (SCAG) and supply chain resilience (SCRES) on performance under the moderating effect of organizational culture. We have used the dynamic cap...

Purpose Production planning and resource allocation are ongoing issues that organisations face on a day-to-day basis. The purpose of this paper is to address these issues by developing a dynamic performance measurement system (DPMS) to effectively re-deploy manufacturing resources, thus enhancing the decision-making process in optimising performance output. The study also explores the development of dynamic capabilities through exploitation of the organisational tacit knowledge. Design/methodology/approach The study was conducted using six-stage action research for developing DPMS with real-time control of independent variables on the production lines to study the impact. The DPMS was developed using a hybrid approach of discrete event simulation and system dynamics by using the historical as well as live data from the action case organisation. Findings Through the development of DPMS and by combining the explicit and tacit knowledge, this study demonstrated an understanding of using cause and effect analysis in manufacturing systems to predict performance. Such a DPMS creates agility in decision making and significantly enhances the decision-making process under uncertainty. The research also explored how the resources can be developed and maintained into dynamic capabilities to sustain competitive advantage. Research limitations/implications The present study provides a starting-point for further research in other manufacturing organisations to generalise findings. Originality/value The originality of the DPMS model comes from the approach used to build the cause and effect analysis by exploiting the tacit knowledge and making it dynamic by adding modelling capabilities. Originality also comes from the hybrid approach used in developing the DPMS.

Purpose A shortage of skills is recognized as a major source of risk in supply chain networks. This study uses two independent organizational theories to explain how to build applicable skills for continuous availability of appropriate supply chain talents. The purpose of this paper is to propose an integrated framework that links human agency theory, social capital theory and supply chain skill. Design/methodology/approach This framework is analyzed in third party logistics (3PL) organizations by confirmatory factor analysis and tested using a survey. After pre-testing by six academics and six practitioners, and following the total design method, the data were collected from 183 3PL organizations in India. Data were checked to ensure no non-response bias. Research hypotheses were tested using WarpPLS-structural equation modeling. Findings A primary finding offers guidance to 3PL managers. Their driving role and mediating role of access to information and access to resources facilitate building supply chain skill. Leaders who invest in library, acquiring e-resources, offer financial support and create trust among employees are enablers of building supply chain skill. Originality/value This study classified 14 supply chain skills into three categories as: managerial skill, quantitative skill and supply chain core skill. The study could be extended to similar companies in other developing countries.

PurposeA low-carbon economy is the pressing need of the hour. Despite several efforts taken by the government and large corporations, there is still research to be conducted exploring the role of top management commitment in translating external pressures into responses that help to build low-carbon emissions in supply chains.Design/methodology/approachThe authors have grounded their framework in institutional theory, agency theory and contingency theory. On the basis of existing literature, four hypotheses were drawn. To test these hypotheses, a questionnaire was developed and pre-tested. Finally, statistical analyses were performed to test the research hypotheses using 176 samples gathered using a pre-tested questionnaire following Dillman’s (2007) total design test method.FindingsThe results suggest that coercive pressures and mimetic pressures under the mediating effect of top management commitment have a significant influence on organizational response to low-carbon emissions. The authors further note that supply base complexity has moderating effects on the link between top management commitment and organizational response towards low-carbon emissions.Originality/valueThis study offers valuable insights to those managers and environmental consultants who view supply base complexity as a limitation. However, the results indicate that supply base complexity may help to enhance the effectiveness of the top management commitment on organizational response towards low-carbon emissions.

Purpose Sustainable supply chain management (SSCM) has attracted considerable interest among academics and practitioners. The purpose of this paper is to present a critical review of the literature, to identify missing links, to argue for the use of world class SSCM (WCSSCM) through a framework, and suggest further research directions. Design/methodology/approach In the paper the authors have undertaken an extensive review of literature and classified articles using a novel classification scheme. Findings Through the extensive review and identification of research gaps, the paper identifies significant differences between definitions and methodologies in the SSCM literature; and argues for “WCSSCM.” This term is elaborated on via a theoretical framework in which 18 dimensions are classified under six constructs of SSCM. Furthermore, a list of potential research directions for WCSSCM is discussed. Research limitations/implications The research is an attempt to critically review literature, argue for WCSSCM, and develop a theoretical framework. Originality/value The paper offers a new approach to SSCM literature, arguing for WCSSCM through a framework, and providing further research directions.

The main objective of the study is to understand how big data analytics capability (BDAC) as an organizational culture can enhance trust and collaborative performance between civil and military organizations engaged in disaster relief operations. The theoretical framework is grounded in organizational information processing theory (OIPT). We have conceptualized an original theoretical model to show, using the competing value model (CVM), how BDAC, under a moderating influence of organizational culture, affects swift trust (ST) and collaborative performance (CP). We used WarpPLS 6.0 to test the proposed research hypotheses using multi-respondent data gathered through an email questionnaire sent to managers working in 373 organizations, including the military forces of different countries, government aid agencies, UN specialized agencies, international non-government organizations (NGOs), service providers, and contractors. The results offer four important implications. First, BDAC has a positive, significant effect on ST and CP. Second, flexible orientation (FO) and controlled orientation (CO) have no significant influence on building ST. Third, FO has a positive and significant moderating effect on the path joining BDAC and CP. Finally, CO has negative and significant moderating effect on the path joining BDAC and CP. The control variables: temporal orientation (TO) and interdependency (I) have significant effects on ST and CP. These results extend OIPT to create a better understanding of the application of information processing capabilities to build swift trust and improve collaborative performance. Furthermore, managers can derive multiple insights from this theoretically-grounded study to understand how BDAC can be exploited to gain insights in contexts of different management styles and cultures. We have also outlined the study limitations and provided numerous future research directions.

The purpose of this paper is to propose and test a theoretical framework to explain resilience in supply chain networks for sustainability using unstructured Big Data, based upon 36,422 items gathered in the form of tweets, news, Facebook, WordPress, Instagram, Google+, and YouTube, and structured data, via responses from 205 managers involved in disaster relief activities in the aftermath of Nepal earthquake in 2015. The paper uses Big Data analysis, followed by a survey which was analyzed using content analysis and confirmatory factor analysis (CFA). The results of the analysis suggest that swift trust, information sharing and public–private partnership are critical enablers of resilience in supply chain networks. The current study used cross-sectional data. However the hypotheses of the study can be tested using longitudinal data to attempt to establish causality. The article advances the literature on resilience in disaster supply chain networks for sustainability in that (i) it suggests the use of Big Data analysis to propose and test particular frameworks in the context of resilient supply chains that enable sustainability; (ii) it argues that swift trust, public private partnerships, and quality information sharing link to resilience in supply chain networks; and (iii) it uses the context of Nepal, at the moment of the disaster relief activities to provide contemporaneous perceptions of the phenomenon as it takes place.

This paper argues for the use of Total Interpretive Structural Modeling (TISM) in sustainable supply chain management (SSCM). The literature has identified antecedents and drivers for the adoption of SSCM. However, there is relatively little research on methodological approaches and techniques that take into account the dynamic nature of SSCM and bridge the existing quantitative/qualitative divide. To address this gap, this paper firstly systematically reviews the literature on SSCM drivers; secondly, it argues for the use of alternative methods research to address questions related to SSCM drivers; and thirdly, it proposes and illustrates the use of TISM and Cross Impact Matrix-multiplication applied to classification (MICMAC) analysis to test a framework that extrapolates SSCM drivers and their relationships. The framework depicts how drivers are distributed in various levels and how a particular driver influences the other through transitive links. The paper concludes with limitations and further research directions.

Research on social sustainability in developing countries has recently gained importance for both academics and practitioners. Studies in the supply chain management field take either a supplier or a manufacturer perspective that address predominantly corporate social responsibility (CSR) issues referring to the internal stakeholders. Our research integrates the literature on supplier, manufacturer, and customer responsibility and proposes the concept of supply chain social sustainability (SCSS) that refers to addressing social issues within the overall (upstream and downstream) supply chain. Furthermore, we develop and empirically validate scales for measuring SCSS using in-depth interviews and a survey in the Indian manufacturing industry. Our results suggest that SCSS consists of six underlying dimensions, namely equity, safety, health and welfare, philanthropy, ethics, human rights, in a 20-item valid and reliable scale. We discuss the implications of the findings for research and practice and suggest future research avenues.

The recent interest in big data has led many companies to develop big data analytics capability (BDAC) in order to enhance firm performance (FPER). However, BDAC pays off for some companies but not for others. It appears that very few have achieved a big impact through big data. To address this challenge, this study proposes a BDAC model drawing on the resource-based theory (RBT) and the entanglement view of sociomaterialism. The findings show BDAC as a hierarchical model, which consists of three primary dimensions (i.e., management, technology, and talent capability) and 11 subdimensions (i.e., planning, investment, coordination, control, connectivity, compatibility, modularity, technology management knowledge, technical knowledge, business knowledge and relational knowledge). The findings from two Delphi studies and 152 online surveys of business analysts in the U.S. confirm the value of the entanglement conceptualization of the higher-order BDAC model and its impact on FPER. The results also illuminate the significant moderating impact of analytics capability–business strategy alignment on the BDAC–FPER relationship.

Purpose – The emergent field of Internet of Things (IoT) has been evolving rapidly with a geometric growth in the number of academic publications in this field. The purpose of this paper is to review the literature of IoT in past 16 years using rigorous bibliometric and network analysis tools, offering at the same time future directions for the IoT research community and implications for managers and decision makers. Design/methodology/approach – The authors adopted the techniques of bibliometric and network analysis. The paper reviewed the articles published on IoT from 2000 to 2015. Findings – This study identifies top contributing authors; key research topics related to the field; the most influential works based on citations and PageRank; and established and emerging research clusters. Scholars are encouraged to further explore this topic. Research limitations/implications – This study focusses only on vision and applications of IoT. Scholars may explore various other aspects of this area of research....

Purpose – At a time when the number and seriousness of disasters seems to be increasing, humanitarian organizations find that besides their challenging work they are faced with problems caused by a high level of turnover of staff. The paper aims to discuss these issues. Design/methodology/approach – Based on the 24 variables leading to employee turnover identified by Cotton and Tuttle (1986) the authors analyse the work-related, external and personal factors affecting employee turnover in humanitarian organizations, using a survey of members of the Indian National Institute of Disaster Management. Findings – Results indicated that the three factors are present. Of the external factors, only employment perception had a factor loading over 0.7; of the work-related factors, all were significant; of the personal factors, biographical information, marital status, number of dependants, aptitude and ability and intelligence had the highest loadings. It was also shown that behavioural intentions and net expectation were not significant. Originality/value – Only a few studies reported on employee turnover and its reasons are not well understood in the context of humanitarian organizations. To address this need, the aim of this paper is to explore the personal reasons impacting employee turnover in humanitarian organizations. In the study the authors have adopted 24 variables used in Cotton and Tuttle (1986) and classified into constructs to explain turnover, and further tested the model using data gathered from humanitarian organizations.

The importance of big data analytics, artificial intelligence, and machine learning has been at the forefront of research for operations and supply chain management. Literature has reported the influence of big data analytics for improved operational performance, but there has been a paucity of research regarding the role of entrepreneurial orientation (EO) on the adoption of big data analytics. To address this gap, we draw on the dynamic capabilities view of firms and on contingency theory to develop and test a model that describes the role of EO on the adoption of big data analytics powered by artificial intelligence (BDA-AI) and operational performance (OP). We tested our research hypotheses using a survey of 256 responses gathered using a pre-tested questionnaire from manufacturing firms in India with the help of the National Association of Software and Services Companies (NASSCOM) and the Federation of Indian Chambers of Commerce and Industry (FICCI). The results from our analysis indicate that EO enables an organisation to exploit and further explore the BDA-AI capabilities to achieve superior OP. Further, our results provide empirical evidence based on data analysis that EO is strongly associated with higher order capabilities (such as BDA-AI) and OP under differential effects of environmental dynamism (ED). These findings extend the dynamic capability view and contingency theory to create better understanding of dynamic capabilities of the organisation while also providing theoretically grounded guidance to the managers to align their EO with their technological capabilities within their firms.

International audience; The organizations engaged in sustainable development programmes are increasingly paying serious attention towards synergetic relationships between focal firms and their partners to achieve the goal of sustainable consumption and production (SCP) via big data and predictive analytics (BDPA). The study examines the role of BDPA in collaborative performance (CP) among the partners engaged in sustainable development programme to achieve the goal of SCP. The study further investigates the contingent effect of organization fit on the impact of BDPA on CP. We used variance based structural equation modelling (PLS SEM) to test research hypotheses using a sample of 190 respondents working in auto-components manufacturing organizations in India drawn from the ACMA and Dun & Bradstreet databases. The results indicate that BDPA has a significant positive impact on the CP among partners and the organizational compatibility and resource complementarity have positive moderating effects on the path joining BDPA and CP. The study contributes to the understanding of BDPA and collaboration literature in the context of sustainable development. These findings extend the dynamic capability view (DCV) to create a better understanding of contemporary applications of big data and predictive analytics capability, while also providing theoretically grounded directions to managers who seek to use information processing technologies to continuously improve the collaboration in supply chain networks. We have also noted some of the limitations of our study and identified numerous further research directions.

PurposeThe purpose of this paper is to develop a theoretical model to explain the impact of big data and predictive analytics (BDPA) on sustainable business development goal of the organization.Design/methodology/approachThe authors have developed the theoretical model using resource-based view logic and contingency theory. The model was further tested using partial least squares-structural equation modeling (PLS-SEM) following Peng and Lai (2012) arguments. The authors gathered 205 responses using survey-based instrument for PLS-SEM.FindingsThe statistical results suggest that out of four research hypotheses, the authors found support for three hypotheses (H1-H3) and the authors did not find support forH4. Although the authors did not find support forH4(moderating role of supply base complexity (SBC)), however, in future the relationship between BDPA, SBC and sustainable supply chain performance measures remain interesting research questions for further studies.Originality/valueThis study makes some original contribution to the operations and supply chain management literature. The authors provide theory-driven and empirically proven results which extend previous studies which have focused on single performance measures (i.e. economic or environmental). Hence, by studying the impact of BDPA on three performance measures the authors have attempted to answer some of the unresolved questions. The authors also offer numerous guidance to the practitioners and policy makers, based on empirical results.

In recent years, energy sustainability has attracted increasing attention from scholars, policy makers, and practitioners. However, in practical competitiveness, companies also have to maintain flexibility to deliver customer requirements. Existing theory has largely seen flexibility and sustainability as separate issues, ignoring their relationship. To address this gap, we attempt to explore energy sustainability using flexible operations management practices in India. Following a case research methodology, we investigate how flexible operations management practices embraced by a leading organization that minimizes energy consumption in plants with better resource utilization and better quality of work life for staff to meet the future requirements based on market forecast. We solve a real-time multi-criteria strategic capacity planning problem with multiple objectives such as throughput maximization, waste minimization, and resource utilization maximization by using discrete event simulation technique. Our data stems from ongoing research within a car manufacturing company in India, located at Pune. Shift timings, setup time, production batch size, and differential rated capacities of plants are considered as the variables in this study. However, optimal routing flexibility combined with volume flexibility helps to achieve significant reduction in energy consumption. Finally, we offer future research questions on flexible operations management practices.

There has been increasing interest from both academics and practitioners in sustainable consumption and production (SCP) behaviour. The literature has mainly focused on antecedents and indicators for SCP behaviour, but scholars are yet to develop frameworks that provide insights into SCP behaviour. To address this gap, this paper develops a theoretical model grounded in institutional and agency theories that explicates the role of top management beliefs and participation when dealing with institutional pressures that impact upon SCP behaviour by facilitating information sharing and reducing behavioural uncertainty. Based on a sample of 167 responses from a survey with Indian organizations, we test the model using partial least squared regression-based structural equation modelling (PLSR SEM). Our results indicate the role of top management commitment as a mediator between institutional pressures and SCP behaviour and the role of beliefs as shaping the commitment of top managers towards strengthening SCP behaviour. We further suggest that participation plays a significant role in quality information sharing, which is important in reducing behavioural uncertainty among stakeholders. Finally we outline our research limitations and further research directions.

This study develops a theoretical model that links reconfigurable manufacturing systems with top management beliefs, participation, and environmental performance, drawing on agency theory and organizational culture. The study takes into account the possible confounding effects of organization size and organizational compatibility. Drawing on responses from 167 top managers, the results of hypothesis testing suggest that (i) higher top management participation, being influenced by top management beliefs, leads to higher chances of RMS becoming adopted by organizations as their manufacturing strategy; (ii) organizational culture moderates the relationship between the level of top management participation and RMS (and manufacturing strategies) adoption; and (iii) higher re-configurability of manufacturing systems leads to better environmental performance. Furthermore, we integrate Agency Theory and organizational culture to explain the role of top management beliefs and participation in achieving environmental performance via RMS. Finally, we offer guidance to those managers who would like to engage in leveraging top management commitment for achieving environmental performance, and outline further research directions.

This paper contributes to the literature on green supply chain management (GSCM) by arguing for the use of mixed methods for theory building. The literature has identified antecedents and enablers for the adoption of GSCM practices. Nevertheless, there is relatively little research on building robust methodological approaches and techniques that take into account the dynamic nature of green supply chains. To address this gap, the paper firstly reviews systematically the literature on GSCM enablers; secondly, it argues for the use of mixed methods research to address questions related to GSCM enablers; thirdly, it uses interpretive structural modeling (ISM), MICMAC analysis, and confirmatory factor analysis (CFA) to illustrate the application of mixed methods in GSCM by testing a model on the enablers of GSCM; and fourthly, highlights the influence of enablers including, inter alia, top management commitment, institutional pressures, supplier and customer relationship management on financial and environmental performance. Finally, we conclude with limitations and further research directions.

Big data (BD) has attracted increasing attention from both academics and practitioners. This paper aims at illustrating the role of big data analytics in supporting world-class sustainable manufacturing (WCSM). Using an extensive literature review to identify different factors that enable the achievement of WCSM through BD and 405 usable responses from senior managers gathered through social networking sites (SNS), we propose a conceptual framework using constructs obtained using reduction of gathered data that summarizes this role; test this framework using data which is heterogeneous, diverse, voluminous, and possess high velocity; and highlight the importance for academia and practice. Finally, we conclude our research findings and further outlined future research directions.

The aim of the paper is to identify the enablers for the successful implementation of Six Sigma. None of the existing frameworks provides any clear understanding related to linkages between, and hierarchical relationships among, the constructs of Six Sigma implementation. Our study has both inductive and deductive elements. We identified enablers of Six Sigma implementation from existing research, and we developed a contextual framework using the interpretive structural modelling technique. We further studied enablers based on their driving power and dependence using MICMAC analysis to categorise the enablers into four clusters. In order to validate the ISM model statistically we developed and pre-tested a structured questionnaire before using it for a survey. Data were collected using a split survey method using a modified version of Dillman's total design method. We performed non-response bias before checking assumptions such as constant variance and normality. We further checked the reliability and construct validity using confirmatory factor analysis. We find that constructs and indicators of our theoretical framework meet the criteria, and find them to be a good fit based on confirmatory factor analysis. We draw conclusions based on statistical analyses and our study limitations, and suggest further research directions.

There is growing interest among researchers in the concept of sustainability. Large commercial corporations have also shown responsibility for preserving planet and people while maintaining profit. Our present paper is motivated by the three P’s—people, planet, and profit. In our paper, we have attempted to develop a responsive sustainable supply chain network which can respond to a certain degree of uncertainty due to uncontrollable forces. We have developed a model using robust optimization based on three well-known robust counterpart optimization formulations. Finally, this paper compares the results of the three formulations using different test scenarios and parameter-sensitive analysis in terms of final output, CPU time, the level of conservatism, the degree of closeness to the ideal solution, the degree of balance involved in developing a compromise solution, and satisfaction degree. Two further questions related to environmental dimensions and social dimensions have been investigated using an appreciative inquiry, a quasi-ethnographic study. In this way, we have embraced mixed research design to address our research questions. We have extended past research by incorporating uncertainty in a mixed integer linear programming (MILP) model and qualitative research methods to fill the voids. We have concluded our research with limitations of our present study and outlined further research directions.

Production Planning & Control would like to welcome Sai Nudurupati, Dinesh Seth, Udechukwu Ojiako, Kit Fai Pun, Michael Bourlakis, Amrik Sohal, Shams Rahman, Roberto Cigolini, Lenka Landryova, Ross...

PurposeThe purpose of this paper is to examine when and how organizations create agility, adaptability, and alignment as distinct supply chain properties to gain sustainable competitive advantage.Design/methodology/approachThe current study utilizes the resource-based view (RBV) under the moderating effect of top management commitment (TMC). To test the research hypotheses, the authors gathered 351 usable responses using a pre-tested questionnaire.FindingsThe statistical analyses suggest that information sharing and supply chain connectivity resources influence supply chain visibility capability, which, under the moderating effect of TMC, enhance supply chain agility, adaptability, and alignment (SCAAA).Originality/valueThe contribution lies in: providing a holistic study of the antecedents of agility, adaptability, and alignment; investigating the moderating role of TMC on SCAAA; following the RBV and addressing calls for investigating the role of resources in supply chain management, and for empirical studies with implications for supply chain design.

International audience; Sustainability benchmarking is gaining importance in industry. Despite its increasing popularity, the existing research utilizing theory to explain the organizations intention to shape performance measurement systems (PMS) for sustainability benchmarking is limited. Drawing upon institutional theory and organizational culture, this study investigates how institutional pressures motivate organizations to shape PMS for sustainability benchmarking and how such effects are moderated by organizational culture. The results of a survey of 277 respondents, gathered from Indian manufacturing firms, suggest that two of the dimensions of the institutional pressures (i.e. coercive pressures and normative pressures) are positively related to the PMS whereas the third dimension (i.e. mimetic pressures) does not affect PMS. Furthermore, organizational culture (i.e. flexible orientation and control orientation) plays a different role on the differential effect of coercive pressures, normative pressures and mimetic pressures on shaping PMS for sustainability benchmarking. The current manuscript offers an interesting contribution to the sustainability benchmarking literature: we integrate the perspectives of ‘external pressures’ and ‘organizational culture’ –as neither perspective, can on, its own can shape the PMS for sustainability benchmarking–, and ‘organizational structure’ under which the external pressures are most effective. From a practitioners' perspective, our study provides theory-driven and empirically-proven guidance for managers to understand the effect of external pressures and the role of organizational structure on PMS for sustainability benchmarking.

Total Quality Management (TQM) is an enduring approach for enhancing firm competitiveness. Still, there is dearth of research regarding organisational diffusion (post-adoption) of TQM. To address this gap, this research proposes a theoretical model rooted in institutional and upper echelon theories that explains TQM diffusion via top management commitment. We surveyed 300 senior quality managers representing 300 auto-components manufacturers in India to collect data to test the proposed model using variance based structural equation modelling (PLS-SEM). The findings suggest that institutional pressures significantly influence top management commitment to TQM. Subsequently, top management commitment influences organisational diffusion of TQM via acceptance, routinization, and assimilation. Managers can use the findings of this research to better understand how to assimilate TQM so that anticipated benefits can be fully realized.

Understanding supply chain sustainability performance is increasingly important for supply chain researchers and managers. Literature has considered supply chain sustainability and the antecedents of performance from a triple bottom line (economic, social, and environmental) perspective. However, the role of supply chain visibility and product complexity contingency in achieving sustainable supply chain performance has not been explored in depth. To address this gap, this study utilizes a contingent resource-based view theory perspective to understand the role of product complexity in shaping the relationship between upstream supply chain visibility (resources and capabilities) and the social, environmental, and economic performance dimensions. We develop and test a theoretical model using survey data gathered from 312 Indian manufacturing organizations. Our findings indicate that supply chain visibility (SCV) has significant influence on social and environmental performance under the moderation effect of product complexity. Hence, the study makes significant contribution to the extant literature by examining the impact of SCV under moderating effect of product complexity on social performance and environmental performance.

Understanding sustainable production is becoming increasingly important for production and operations managers, mainly due to a shortage in natural resources. Sustainability requires many changes in behaviour at all levels. Few studies within the sustainable production literature have empirically disentangled the underlying behavioural concepts of sustainable production. To address this gap, this study utilizes the theory of planned behaviour (TPB) to develop a theoretical framework to explain sustainable production behaviour. Survey data gathered from 128 Indian cement manufacturing units suggest that attitude, subjective norms or social pressures and perceived behavioural control are predictors of the intention for sustainable production which then predicts sustainable production behaviour. The research contribution of this study is twofold: firstly, the current study highlight that the influence of social pressures or subjective norms on intention is greater than attitude and perceived behavioural control; and secondly it may be noted that intention is not a strong predictor of the sustainable production behaviour. Finally, our study based on limitations offers extensive future research directions.