No abstract

No abstract

No abstract

PurposeThe COVID-19 pandemic has badly affected the global economy. The use of social capital as a resource to diversify agribusiness to get more customers and improve the agricultural supply chain is a considerable issue to explore. This study aims to develop a comprehensive measurement of social capital and examine its effect on the intention to diversify agribusiness. From a supply chain perspective, it uses theory of planned behavior (TPB) and resource-based view (RBV).Design/methodology/approachThe study uses a mixed-methods approach. In-depth interviews, focus group discussions and surveys are used. Structural equation modeling on a sample of 465 respondents in Vietnam was employed to examine the hypothesized relationships.FindingsAn integrative measurement scale of social capital from an agricultural supply chain perspective is suggested. The study also shows significant causal relationships amongst social capital, motives, TPB's determinants and the intention to diversify agribusinesses in light of supply chain perspectives.Originality/valueThe study offers a significant contribution to the existing body of knowledge in the literature on social capital, motives, TPB, RBV and supply chain perspectives. The study was executed in Vietnam, where most farmers are smallholders, family business owners or micro-scale entrepreneurs in agriculture.

PurposeThe study aims to understand how big data analytics capabilities of tech startups help them gain competitive advantage and improve their firm performance. The study is performed for two countries: India and China. A comparative analysis is also discussed in the study.Design/methodology/approachThe study collected responses from tech startups from both India and China. A total of 502 responses were collected with 269 from India and 233 from China. The results were analyzed using Warp PLS 6.0 after testing for common method bias, endogeneity and reliability of data. The study tested five primary hypotheses and also tested the effect of two control variables: country of origin of startup and age of the startup.FindingsWe found that big data analytics capabilities have a positive and significant impact on the firm performance and competitive advantage of tech startups. While organizational culture proved to have a positive impact as a moderator, innovation was found to have non-significant effect. The results also found to have non-significant effect of age of the firm while its country of origin does play an important role in defining its success.Originality/valueThe study offer key insights for the tech startups operating in two countries which are geographically neighbors but differ in the tech expertise from each other. Moreover, the study offers key insights on how does the origin of the country contributes significantly to explaining the success and competitiveness of the firm.

No abstract

No abstract

PurposeTraditional supply chain arrangements have failed to keep up with escalating customer demands and breakthrough innovations. The way forward is a flexible yet innovative network that leverages ecosystem partners and digital tools to unlock new agility. The paper aims at identifying and analyzing numerous critical success factors (CSFs) that may improve the efficiency of a digital supply chain.Design/methodology/approachTwelve CSFs are identified in this paper through an extensive literature survey. Expert opinion has been considered and the hierarchical structure built using total interpretative structural modeling (TISM) which highlights the interdependencies between these CSFs. Cross-impact matrix multiplication (MICMAC) is used to determine the driving and dependence power of each factor.FindingsThis study identified 12 CSFs through an extensive literature survey. The ISM model resulted in six different levels beginning from redesign organization at the bottom of the structure. The TISM model explained why redesigning the organization is pivotal to bringing about novel agility in the supply chain. MICMAC analysis confirmed that the following enhanced the success of a digital supply chain: Sales and Operation Planning Strategies, Strategic Sourcing Techniques, Smart Manufacturing Processes and Warehouse Management.Research limitations/implicationsVarious other components contributing to the 12 CSFs identified in this paper may be discovered and detailed in future research. Additionally, further research is required to expand the existing technology-based services structural model to a more empirical form.Practical implicationsThis study offers a comprehensive but not exhaustive list of CSFs essential to digital supply chain growth. It will enable market experts and leaders to concentrate on key factors leading to tactical decisions and maximum value for firms.Originality/valueThe paper seeks to add to the body of knowledge on real digitally-led supply chain transformation, which is still in its early stages. This study is one of the first, if not the first, to examine success factors critical to the improvement of the performance of the supply chain. It lays the foundation for further research in this field.