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PurposeThe research study aims to investigate green supply chain management (GSCM) elements as part of a complete system. It aims to understand the special properties of the GSCM system under the moderating effects of product complexity and purchasing structure.Design/methodology/approachA thorough literature review led to the building of the conceptual framework. Six constructs were identified using systems theory. These constructs include green supply chain technological dimensions (particularly, Artificial Intelligence (AI) based), green supply chain strategy, green supply chain process, product complexity, purchasing structure, and firm performance. The instrument was scientifically developed for gathering survey responses using complete design test methods. The conceptual model was eventually tested based on survey data collected from 250 automotive components and allied manufacturers in the emerging economy of South Africa.FindingsThe results indicate that GSCM technological dimensions (AI-based) positively influence GSCM strategy. Further, GSCM strategy was found to positively influence the GSCM process. The GSCM processes have significant effects on environmental performance, social performance, and financial performance. The product complexity has a significant moderation effect on the paths GSCM strategy and GSCM process.Originality/valueThe findings from multivariate data analysis provide a better understanding of GSCM system dynamics and are helpful to key decision-makers. This unique model has elevated GSCM theory to a new level. There are limited studies available in the existing GSCM literature using systems theory. This study will offer an advanced/comprehensive understanding to readers in this relatively new concept.

PurposeAs a global pandemic, the COVID-19 crisis has profoundly affected the development of local firms, threatening the survival of small and medium enterprises (SMEs). This study aims to present an integrated framework by investigating the impact of strategic tools (i.e. firms' capability of business agility, marketing operational efficiency, optimisation of innovation capability [OIC], managing employees' satisfaction and rethinking customers' experience) on the survival strategies of SMEs amidst the COVID-19 pandemic.Design/methodology/approachThe current study used data from managers of SMEs and conducted an asymmetrical analysis (i.e. structural equation modelling [SEM]) to investigate the factors influencing the survival strategies of SMEs amidst the COVID-19 pandemic. This study also applied an asymmetrical approach (i.e. fuzzy sets qualitative comparative analysis-fsQCA) to explore the causal recipes and analysis of the necessary conditions to identify the factors required to achieve the expected outcome.FindingsResults from SEM support all hypotheses. Results from fsQCA with the same data set show that firms' business agility and OIC are necessary conditions for SMEs' survival strategies. The result from fsQCA also reveals multiple sufficient conditions to succeed SMEs' survival strategies amidst the COVID-19 pandemic.Practical implicationsFindings prescribe how SMEs adapt to this vulnerable business condition by applying the strategic tools and recipes suggested for survival.Originality/valueThis research applied an innovative analysis to reveal necessary and sufficient conditions that conventional methods such as SEM have limited power. This pioneering research in the context of the COVID-19 pandemic is considered novel in terms of the prescriptive strategic recipes offered to SMEs to adapt to and survive in the crisis caused by COVID-19.

International audience ; Government of India's 'Digital India' initiative intends to build robust digital ecosystem that fosters innovation & entrepreneurship enabling better citizen service & citizen empowerment. Digitization in India involves geo-demographic & socio-economic dependency, choice of smart technologies undergoing rapid innovation, strategic roll-out planning & flawless implementation as prerequisite of technology diffusion & benefit realization. This study identifies technical & non-technical determinants of smart digital framework roll out that can accelerate digital diffusion in urban public services in India. This study follows inductive exploratory method, combining grounded theory & text mining for primary data analysis. Study reveals digitization is an ecosystem of private & public enterprises and citizen participation, identifies integrated use analytics & IoT can enable connected smart city, whereas technology cost, digital literacy & sustainable innovation as non-technological determinant towards resilient urban digital infrastructure in India.

International audience ; Government of India's 'Digital India' initiative intends to build robust digital ecosystem that fosters innovation & entrepreneurship enabling better citizen service & citizen empowerment. Digitization in India involves geo-demographic & socio-economic dependency, choice of smart technologies undergoing rapid innovation, strategic roll-out planning & flawless implementation as prerequisite of technology diffusion & benefit realization. This study identifies technical & non-technical determinants of smart digital framework roll out that can accelerate digital diffusion in urban public services in India. This study follows inductive exploratory method, combining grounded theory & text mining for primary data analysis. Study reveals digitization is an ecosystem of private & public enterprises and citizen participation, identifies integrated use analytics & IoT can enable connected smart city, whereas technology cost, digital literacy & sustainable innovation as non-technological determinant towards resilient urban digital infrastructure in India.

PurposeThe cold supply chain industry is still emerging and digital transformation is in the nascent stage in this industry. This paper argues that there are various barriers to implementing blockchain technology in the cold supply chain and aims to develop and validate a model for overcoming key barriers to implementing blockchain technology in the cold supply chain.Design/methodology/approachThe adoption of blockchain technology was proposed through interpretive structural modeling (ISM) and further it is validated using structural equation modeling (SEM).FindingsIn this study, ten key barriers to implementing blockchain technology in the cold supply chain were identified, modelled and analysed. Poor leadership style of top management was found to be the most important barriers to implementing blockchain technology in the cold supply chain. The results of SEM indicate that all the paths are supported. The findings showcase the barriers responsible for the lack of blockchain technology infrastructure that ultimately impacts the cold supply chains.Practical implicationsThis study highlights the fact that the fate of blockchain technology infrastructure development depends on the leadership style of top management. Demonstrating good leadership style by top management can help overcome the barriers. A good leader pulls the entire team instead of pushing the team. A good leader can guide the entire team to improve IT governance, financial investment, digital footprint, digital readiness, skills and collaboration with service providers to implement blockchain technology. Not only that, a good leader provides mental strength to the team and helps overcome the fear of implementing blockchain in the cold supply chain. A good leader demonstrates good administrative skills and focus on security and privacy policies.Originality/valueThis is a novel contribution towards analysing the key barriers to implementing blockchain technology in the South African cold supply chain using the integrated ISM–MICMAC and SEM approach.