PurposeAs e-commerce has expanded rapidly, online shopping platforms have become widespread in India and throughout the world. Product return, which has a negative effect on the E-Commerce Industry's ...economic and ecological sustainability, is one of the E-Commerce Industry's greatest challenges in light of the substantial increase in online transactions. The authors have analyzed the purchasing patterns of the customers to better comprehend their product purchase and return patterns.Design/methodology/approachThe authors utilized digital transformation techniques-based recency, frequency and monetary models to better understand and segment potential customers in order to address personalized strategies to increase sales, and the authors performed seller clustering using k-means and hierarchical clustering to determine why some sellers have the most sales and what products they offer that entice customers to purchase.FindingsThe authors discovered, through the application of digital transformation models to customer segmentation, that over 61.15% of consumers are likely to purchase, loyal customers and utilize firm service, whereas approximately 35% of customers have either stopped purchasing or have relatively low spending. To retain these consumer segments, special consideration and an enticing offer are required. As the authors dug deeper into the seller clustering, we discovered that the maximum number of clusters is six, while certain clusters indicate that prompt delivery of the goods plays a crucial role in customer feedback and high sales volume.Originality/valueThis is one of the rare study that develops a seller segmentation strategy by utilizing digital transformation-based methods in order to achieve seller group division.
•This study addresses information receiving and its potential benefits using SaaS.•The results imply that RTIR is the antecedent of customer engagement.•Customer orientation is positively mediating ...between RTIR and customer engagement.•Exposes practitioners to RTIR and CE in terms of direct & indirect benefits using SaaS.•Provides a new theoretical framework using ToIS to advance RTIR in downstream.
Industry 4.0 requires firms to adopt the latest technology to be more effective. However, previous studies have not addressed customer engagement (CE) and its direct benefit (buying) and indirect benefits (referring, influencing, and feedback) using modern technologies such as industry 4.0. The present study analyses customer engagement in regard to real-time information receiving (RTIR) in the downstream operations implemented through software-as-a-service technology. The data is collected from 533 customers of small businesses in retail, food & beverages, and accommodation sectors. The study's empirical model is validated using the theory of information sharing (ToIS). The outcomes specify that RTIR is the antecedent of CE. The results show the mediation effect of customer orientation on RTIR and CE relationship. The study also confirms that gender moderates three out of the four examined relationships between RTIR and CE. Subsequently, our outcomes offer a deeper understanding of RTIR and CE, imbedded in ToIS. This article exposes industry practitioners to RTIR and CE in terms of direct benefit and indirect benefits with modern technologies in downstream operations. This study provides a new theoretical framework using ToIS to advance RTIR in downstream operations through SaaS and CE.
Blockchain technology offers undeniable benefits of enhanced transparency, reliability, and information accuracy to agri-food supply chains. Currently, the implementation of this technology has ...associated challenges. This paper explores the influential barriers to implementing blockchain technology (BCT) in the agri-food supply chain (AFSC). An integrated literature review approach and expert opinions were employed to explore the influential barriers. The barriers were modelled using the hybrid fuzzy-based decision-making trial and evaluation laboratory (Fuzzy-DEMATEL) approach to evaluate the interrelationship and classify them into cause-and-effect groups. As an outcome, a comprehensive framework was proposed revealing the unfamiliarity with technology, high investment cost, lack of regulations, technological infeasibility, and scalability as key influential barriers. This study will help the decision-makers to focus on influential barriers and identify the roadmap towards blockchain implementation.
The apparel manufacturers and retailers throughout the world are searching for innovative solutions to reduce the harmful impact the industry has on the environment. These firms cannot afford to lose ...the environmentally conscious consumers. Circular fashion is an emerging area that promotes the reuse and recycling of the used clothing. Online renting of the used clothes is an emerging business that supports circular fashion practices leading to environmental and economic sustainability. The present study investigates the antecedents of online second-hand clothing rental platforms that drive the consumer to adopt them. Based on the theoretical underpinning of the unified theory of acceptance and use of technology and source credibility theory, the study finds that the utility of these platforms, ease of use, attitude, and social pressure drives the behavioral intent of the consumers to use these platforms. The study also identifies that communications from Instagram microcelebrities could positively influence the consumers to adopt these platforms promoting circular fashion and sustainability.
•Circular fashion is an emerging area that promotes the reuse and recycling of used clothing.•Online secondhand clothing retailing platform (OSCRP) clothing supports circular fashion.•Research framework based on Unified Theory of Acceptance and Use of Technology and Source Credibility Theory.•Ease of use, attitude, and social pressure drives the behavioral intent.•Instagram microcelebrities influence OSCRP adoption.
Purpose
– The purpose of this paper is to describe an application of Multi-Criteria Decision Making (MCDM) technique for the selection of waste treatment and disposal technology for municipal solid ...waste (MSW).
Design/methodology/approach
– The proposed approach is based on the integration of Delphi and Analytic Hierarchy Process (AHP) techniques. A model has been proposed to evaluate the best treatment and disposal technology. Expert opinions have been incorporated in the selection of criteria. AHP has been used to determine the weights of criteria, followed by ranking of the available technologies.
Findings
– Delphi method was used to derive appropriate evaluation criteria to assess the potential alternative technologies. A set of identified holistic criteria was used, representing the environmental, social, and economic aspects, as compared to the sub-criteria concept generally found in existing literature. Quantitative weightings from the AHP model were calculated to identify the priorities of alternatives. The study provides a simple framework for technology selection as compared to the complex models present in the literature, reducing the uncertainty, cost and time consumed in the decision-making process.
Practical implications
– The model identifies the optimal technologies for the handling, treatment and disposal of MSW in a better economic and more environmentally sustainable way. The study provides a simple framework for selection as compared to the complex models present in the literature, reducing the uncertainty, cost and time taken by the decision-making process.
Originality/value
– The paper highlights a new insight into MCDM techniques to select an optimum treatment and disposal technology suitable for MSW management in India. The study identifies a minimal relevant set of evaluation criteria, and appropriate technologies for the handling, treatment, and disposal of MSW in a more economic and environmentally sustainable way.
Research on Blockchain implementation in the Pharmaceutical Supply Chains (PSC) is lacking despite its strong potential to overcome conventional supply chain challenges. Thus, this study aims to ...provide critical insight into the nexus between Blockchain and PSC and further build a conceptual framework for implementation within the pharmaceutical industry. Following a systematic literature review and text mining approach, 65 interdisciplinary articles published between 2010 and 2021 were studied to capture the decade long developments. Descriptive and thematic analysis showcases nascent developments of Blockchain in PSC. The drivers and barriers to adoption, implementation stages, and applications identified through the thematic analysis guide in setting the agenda for future research, primarily focussing on the use of Blockchain for drug counterfeiting, recall issues, along with other sector-specific challenges such as patient privacy, regulations and clinical trials. Research on Blockchain for PSC has been slow compared to other sectors, but has accelerated since the Covid-19 pandemic. Identified influential factors, implementation process and apparent applications are expected to influence researchers and practitioners in developing a roadmap for adopting Blockchain in the pharmaceutical industry. The proposed conceptual framework is novel and provides valuable directions to producers, regulators and governments to implement Blockchain in the pharmaceutical industry.
Artificial Intelligence (AI) offers a promising solution for building and promoting more resilient supply chains. However, the literature is highly dispersed regarding the application of AI in ...supply-chain management. The literature to date lacks a decision-making framework for identifying and applying powerful AI techniques to build supply-chain resilience (SCRes), curbing advances in research and practice on this interesting interface. In this paper, we propose an integrated Multi-criteria decision-making (MCDM) technique powered by AI-based algorithms such as Fuzzy systems, Wavelet Neural Networks (WNN) and Evaluation based on Distance from Average Solution (EDAS) to identify patterns in AI techniques for developing different SCRes strategies. The analysis was informed by data collected from 479 manufacturing companies to determine the most significant AI applications used for SCRes. The findings show that fuzzy logic programming, machine learning big data, and agent-based systems are the most promising techniques used to promote SCRes strategies. The study findings support decision-makers by providing an integrated decision-making framework to guide practitioners in AI deployment for building SCRes.
With the advent of Big Data Analytics (BDA) alongside the maturity of specific improvement approaches such as Lean Six Sigma (LSS) and Green Manufacturing (GM), the integration of these initiatives ...to achieve higher environmental performance (EP) is gathering the interest of both researchers and practitioners. The present study builds on the resources based view of capabilities to propose and empirically test a framework exploring whether LSS and GM mediate the relationship between BDA capabilities and EP. A two-stage hybrid Factorial Analysis - Structural Equation Modeling is used to draw insights from 201 industry practitioners from North African companies. The findings confirm the direct influence of BDA on EP and also identify LSS and GM as significant mediating variables that act as a catalyst to boost indirect impacts of BDA on EP. This study can help researchers and practitioners to fully understand and benefit from BDA capabilities and improvement initiatives such as LSS and GM while managing environmental issues. The study discusses theoretical and managerial implications for enhancing the environmental performance of the manufacturing organizations.
In recent years, the emerging Digital Twin (DT) paradigm under Industry 4.0 has been attracting more attention from both practitioners and academia due to its dynamic capabilities. Most DT studies ...are theoretical and deal with hypothetical analysis, whereas fewer studies are available on real-life empirical cases. Due to dynamic problem-solving capabilities, DT technologies are widely used in performance improvement analysis in food processing companies (FPC) despite limited implication's for business strategies. Our study incorporates the DT technologies with an implementation case study on FPC and accomplishes the real-life problem of the food processing company (FPC). Moreover, the proposed DT research framework demonstrates the various DT implementation stages, such as strategic mapping and physical-virtual space replica, with rigorous analysis. The results show that DT enhances the existing system's machine availability, allocation efficiency, technical efficiency, worker efficiency, utilization rate, effectiveness, step ratio, and throughput rate. The proposed physical-virtual interface model is executed using AnyLogic software with JAVA-enabled programming.
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