3 research outputs found

    Determinants of Purchase Intention: An Interpretive Structural Modelling Approach

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    In the present paper, the factors which impact consumer behavior are explored through extensive literature review. Also, common determinants of online and offline consumer behavior are identified. Subsequently, ISM approach is used to find the inter-relationship among these factors. Finally, ISM model depicting this interrelationship is developed and MICMAC analysis is performed to categorize factors into clusters depending on their drive and dependence power. Identified factors common to both offline and online buying behavior include convenience, promotion, availability, brand image, demography, safety, quality, word of mouth and price. ISM reveals that promotion, brand image, demography, quality and price are the linking factors with strong dependence and driving power. Additionally, convenience, availability and safety have emerged as the independent factors with strong driving power and weak dependence power. Keywords: Offline buying. online buying. Determinants. ISM (Interpretive structural modelling). MICMAC DOI: 10.7176/JMCR/68-02 Publication date:May 31st 202

    Critical factors of digital supply chains for organizational performance improvement

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    Technological advancement is redefining supply chains (SCs) processes and soon traditional ways of managing SCs will no more be feasible and effective. Due to recent advancement in technology, digitalization has become an emerging topic among decision-makers and researchers. To cope-up with this emerging trend in customer behavior and remain competitive, organizations must move from their traditional ways of managing their SCs to digital supply chains (DSCs) for improved organizational performance. Therefore, the purpose of this article is in two folds: First, to identify critical factors of DSCs that are essential for transitioning traditional SCs to DSCs to improve organizational performance. Second, interpretive structural modeling is used to establish the relationship among critical factors and (matriced’ impacts croise´s multiplication applique´e a´un classement used to identify the driving and dependency power of the critical factors. Thus, this article identified fifteen DSC critical factors and established their direct and indirect effect on DSCs. The results show that “SC resilience”, and “proactive prevention” have the highest dependency power factors whilst “integration” and “advanced operational models” have the highest driving power factors. This article can help SC managers and decision-makers to understand the critical factors essential in adopting DSCs for improving organizational performance

    Analysis of Challenges for Blockchain Adoption within the Indian Public Sector: An Interpretive Structural Modelling Approach

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    YesPurpose – Blockchain is one of the most significant emerging technologies that is set to transform many aspects of industry and society. However, it has several major technical, social, legal, environmental and ethical complexities that offer significant challenges for mainstream use within the public sector. The Covid-19 pandemic has compelled many public sector employees to work remotely, highlighting a number of challenges to blockchain adoption within the Indian context signifying the pertinence of this research topic in the post-pandemic era. This study offers insight to researchers and policymakers alike on how such challenges are interdependent within this important subject. Design/methodology/approach – We explored 16 unique sets of challenges selected from the literature and gathered data from nine experts from government settings, healthcare and education sectors and academia who have significant knowledge and experience of blockchain implementation and use in their respective organisations. The implementation of Interpretive Structural Modelling (ISM) and MICMAC provided a precise set of driving, linkage and dependent challenges that were used to formulate the framework. Findings – The developed ISM framework is split into six different levels. The results suggest that the bottom level consists of challenges such as ‘Lack of standards (C9)’ and ‘Lack of validation (C10)’ form the foundation of the hierarchical structure of blockchain adoption. However, the topmost level consists of a highly dependent challenge termed ‘adoption of blockchain in the public sector (C16)’. The research filters the selected set of five challenges to develop a parsimonious model and formulated six propositions to examine the impact of ‘lack of standard (C9)’, ‘lack of validation (C10)’ on ‘security issues (C3)’ and ‘privacy concerns (C2)’, which eventually determine individuals’ ‘reluctance to use blockchain technology (C12)’. Originality/Value – This research fills a key gap in exiting research by exploring the key challenges in blockchain adoption within the public sector by developing a valuable framework to model this important topic. To the best of our knowledge, this is the first paper to address these challenges and develop a parsimonious model for challenges of blockchain adoption in the public sector settings
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