Journal of Enterprise Information Management最新文献

Purpose

While business intelligence and analytic (BIA) systems have been developed by large corporations around the world, micro-, small- and medium-sized enterprises (MSMEs) have recently paid attention and deployed BIA adoption, particularly during the Covid-19 pandemic disruption. This study sheds light on how MSMEs adopt the BIA systems and then proposes a framework for the BIA adoption process in the context of MSMEs.

Design/methodology/approach

The multiple case research design and interpretivism approach are employed for expanding the theoretical boundary of the strategic management fields in BIA adoption by MSMEs. In total, 35 semi-structured interviews were conducted with senior managers and owners involved in BIA adoption from 17 participating MSMEs.

Findings

The research study identifies three BIA adoption stages with specific technical and managerial features in the path of BIA adoption in each stage, corresponding to the level of BIA maturity of MSMEs. The authors also highlight other factors that directly influence the successful adoption and transformation from each stage to another.

Research limitations/implications

The research study identifies three BIA adoption stages with specific technical and managerial features in the path of BIA adoption at each stage that corresponds to the level of BIA maturity of MSMEs. Besides, this study also extends the current literature on BIA adoption in an organisation during the Covid-19 pandemic by identifying several contextual barriers that directly influence the BIA adoption.

Practical implications

Research findings can help business leaders and owners of MSMEs to determine the BIA maturity of their organisation. Furthermore, the authors’ framework can also be used by consultancies and standard setters to develop detailed BIA adoption strategies and tactics that support MSMEs' digitalisation towards BIA adoption.

Originality/value

The research study’s results highlight that contextual factors, leadership competencies, motivations and barriers for BIA adoption can also be used to help MSMEs' leaders and owners to trigger, advance or eliminate challenges for the adoption of BIA initiatives in MSMEs.

Purpose

The authors analysed the operations of two synchronised channels by focusing on “buy online and return in store” (BORS) strategies in fast-fashion retail by investigating internal and external factors affecting this omnichannel strategy.

Design/methodology/approach

The authors apply a combination of techniques to identify the BORS factors. Firstly, a strengths, weaknesses, opportunities and threats (SWOT) analysis was used to define the operational factors of BORS adoption. The authors then apply analytic hierarchy process (AHP) to evaluate the factors under four SWOT categories for kids, male and female consumer groups. The factors of BORS were then ranked using the fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (fuzzy VIKOR) approach.

Findings

Combining the SWOT, AHP and fuzzy VIKOR techniques, the authors identified 21 factors in this study. The opportunity that BORS provides for trying in the fitting room for a better convenient shopping experience was ranked as the most important factor, followed by the opportunity to create a loyal customer profile with an easy and well-organised return process. Furthermore, the results reveal that the child consumer group is the most critical of the stated operations factors, followed by male and female consumers.

Practical implications

The authors described the operational factors and supported the decision-making system of BORS for each consumer group with a priority ranking to realise effective managerial management for fast-fashion retailers and practitioners.

Originality/value

The study contributes to the growing literature on the BORS omnichannel strategy, specifically for fast-fashion retail based on consumer needs.

Purpose

Supply chain integration (SCI) dominates supply chain strategy and is receiving increasing academic attention. The purpose of this paper is to provide a systematic review of the knowledge trajectory and structure of the SCI field.

Design/methodology/approach

Based on 3,533 papers extracted from the Web of Science (WoS), this paper adopts the main path analysis (MPA) method to detect three distinct knowledge development trajectories. Coupling-based clustering is combined with MPA to reveal three critical subfields.

Findings

The findings show that the definition, content and dimensions of SCI lack unified conclusions. The influencing factors and performance consequences of SCI are long-standing research elements. Building theoretical models and integrated systems and applying blockchain technology to improve SCI are the key research contents. The intertwining of collaboration and SCI cannot be ignored, and the green SCI may be a hot topic in the future.

Research limitations/implications

This study explores knowledge in the SCI field based on the limited literature collected by WoS rather than all published papers. The omissions of some relevant papers and books may exist.

Practical implications

The study methodology provides a framework for similar studies in the future, and the results help researchers to get a comprehensive picture of the knowledge trajectory and structure of the SCI field.

Originality/value

Compared to existing reviews, MPA combines cluster analysis to develop a synthetic framework of the knowledge trajectory and structure in the SCI domain. It contributes to a systematic review of the development of SCI.