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Effective inventory management is crucial for SMEs due to limited resources and higher risks like cash flow, storage space, and stockouts. Hence, the aim is to explore how technology and know-how can be integrated with inventory practices and impact operational performance.

The basis of the analysis was collecting papers from a wide range of databases, which included Scopus, Web of Science, and Google Scholar. In the first phase of the process, a search string with as many as nine related keywords was used to obtain 175 papers. It further filtered them based on their titles and abstracts to retain 95 papers that were included for thorough analysis.

The study introduced innovative methods of measuring inventory practices by exploring the impact of know-how. It is the first of its kind to identify and demonstrate how technical, technological, and behavioral know-how can influence inventory management practices and ultimately impact the performance of emerging SMEs. This study stands out for its comprehensive approach, which covers traditional and modern inventory management technologies in a single study.

The study provides valuable insights into the interplay between technical, technological, and behavioral know-how in inventory management practices and their effects on the performance of emerging SMEs in Industry 5.0 in the light of RBV theory.

The RBV theory and the Industry 5.0 paradigm are used in this study to explore how developing SMEs' inventory management practices influence their performance. This study investigates the effects of traditional and modern inventory management systems on business performance. Incorporating RBV theory with the Industry 5.0 framework investigates firm-specific resources and technological advances in the current industrial revolution. This unique technique advances the literature on inventory management and has industry implications.

The purpose of this paper is to examine the impact of knowledge of inventory management practices (KIMP) on operational performance (OP) and business performance (BP). This study emphasized understanding the mediational effect of OPs among KIMP and BP in manufacturing firms of Indian small- and medium-sized enterprises (SMEs).

This study analysed the above relationship from the data collected from 351 key officials of 170 Indian SMEs. The detailed analysis, including reliability, validity and testing hypothesis, was done in advanced SmartPLS-SEM 3.3.3 software.

The findings show that KIMP directly influences OP; thus, a company's OP significantly impacts the overall BP. The KIMP has no significant effect on BP. In line with this, the study findings demonstrate a significant, high mediation effect of OPs between KIMP and BP.

The KIMP on OP has been sparsely studied earlier, and neither have they conceptualized in understanding its impact on BP. In such tumultuous times, key manufacturing executives should stress the importance of KIMP as a comprehensive perspective.

The problem of evaluating potential suppliers has always been based on finding an optimal tradeoff between supplier’s performance consistently meeting firms’ needs and acceptable cost. The purpose of this paper is to propose a hybrid multi-criteria decision framework to quantify this qualitative judgment and reduce ambiguity in selection of suppliers in the era of Industry 4.0.

A hybrid intuitionistic fuzzy entropy weight-based multi-criteria decision model with TOPSIS is proposed. The authors make use of the intuitionistic fuzzy weighted approach operator for aggregating individual decision maker’s opinions regarding each alternative over every criterion. Additionally, the authors employ the concept of Shannon’s entropy to calculate the criteria weights.

Results obtained on the basis of the proposed hybrid methodology are analyzed against two more cases wherein the authors try to showcase the relevance of using IFS and entropy-based decision framework and find out the uniqueness of the proposed framework in supplier selection process.

The proposed model is apposite to solve management problem of supplier selection in two ways: aggregating individual decision maker’s opinion for each of the predefined criteria along with individual decision maker’s importance and ranking the suppliers based on both positive and negative ideal solutions using TOPSIS.

A robust framework incorporates not only suppliers’ performance but also provides weightage to key decision makers. Especially in the context of MCDMs wherein both qualitative and quantitative data is evaluated simultaneously, the proposed framework is unique in its practical implementation of reducing ambiguity in the supplier selection process.

This study aims to examine the effect of supply chain agility (SCA) on operational performance (OP) measurements of steel manufacturing firms. It also investigates the role of cost efficiencies concerning enhance OPs.

The study is based on an experimental research design by collecting data from responses 398 responses of key officials of India’s steel manufacturing firms. Analyses are carried to explore this modern concept with the help of Smart-partial least square (PLS) version 3.3.2 with confirmatory factor analysis and PLS structural equational modelling.

SCA factor (SCAF) directly has influenced the firm’s OP. It also represents cost efficiencies that have partial mediation between the SCAF and OP. The impact of cost efficiencies on OPs is strongly significant as compared to the impact of SCAF on cost efficiencies.

Management teams in the manufacturing industry should stress the role of SCA as a comprehensive concept in responding to market needs in a volatile environment. SCA reflects one of its winning strategies in today’s dynamic and competitive world. Managers must thoroughly know the ramifications of agility to develop a mechanism for determining the procedures and identifying inequality in SC operation.

This study speaks explicitly about the linkage between SCAF, OP, CE. It is an addition to the existing theories of RBV. Enhancements in OP measurements, specifically performance and flexibility, will lead to better firm performance. study conceptualizing the complementing effects of SCA (IS capability) and OPs and second cost efficiencies play positive partial mediating effect in between the link. The achievement of SC agile is especially a critical approach to Boost customer satisfaction and differentiate market position.

As the number of web applications is increasing day by day web mining acts as an important tool to extract useful information from weblogs and analyse them according to the attributes and predict the usage of a website. The main aim of this paper is to inspect how process mining can be used to predict the web usability of hotel booking sites based on the number of users on each page, and the time of stay of each user. Through this paper, the authors analyse the web usability of a website through process mining by finding the web usability metrics. This work proposes an approach to finding the usage of a website using the attributes available in the weblog which predicts the actual footfall on a website.

PROM (Process Mining tool) is used for the analysis of the event log of a hotel booking site. In this work, authors have used a case study to apply the PROM (process mining tool) to pre-process the event log dataset for analysis to discover better-structured process maps than without pre-processing.

This article first provided an overview of process mining, then focused on web mining and later discussed process mining techniques. It also described different target languages: system nets (i.e. Petri nets with an initial and a final state), inductive miner and heuristic miner, graphs showing the change in behaviour of the dataset and predicting the outcome, that is the webpage having the maximum number of hits.

In this work, a case study has been used to apply the PROM (process mining tool) to pre-process the event log dataset for analysis to discover better-structured process maps than without pre-processing.

Deep learning (DL) is on the rise because it can make predictions and judgments based on data that is unseen. Blockchain technologies are being combined with DL frameworks in various industries to provide a safe and effective infrastructure. The review comprises literature that lists the most recent techniques used in the aforementioned application sectors. We examine the current research trends across several fields and evaluate the literature in terms of its advantages and disadvantages.

The integration of blockchain and DL has been explored in several application domains for the past five years (2018–2023). Our research is guided by five research questions, and based on these questions, we concentrate on key application domains such as the usage of Internet of Things (IoT) in several applications, healthcare and cryptocurrency price prediction. We have analyzed the main challenges and possibilities concerning blockchain technologies. We have discussed the methodologies used in the pertinent publications in these areas and contrasted the research trends during the previous five years. Additionally, we provide a comparison of the widely used blockchain frameworks that are used to create blockchain-based DL frameworks.

By responding to five research objectives, the study highlights and assesses the effectiveness of already published works using blockchain and DL. Our findings indicate that IoT applications, such as their use in smart cities and cars, healthcare and cryptocurrency, are the key areas of research. The primary focus of current research is the enhancement of existing systems, with data analysis, storage and sharing via decentralized systems being the main motivation for this integration. Amongst the various frameworks employed, Ethereum and Hyperledger are popular among researchers in the domain of IoT and healthcare, whereas Bitcoin is popular for research on cryptocurrency.

There is a lack of literature that summarizes the state-of-the-art methods incorporating blockchain and DL in popular domains such as healthcare, IoT and cryptocurrency price prediction. We analyze the existing research done in the past five years (2018–2023) to review the issues and emerging trends.

The purpose of this study is to conduct a systematic study of important research trends and published electronic word of mouth (eWOM) studies over the past 20 years in the emerging economy. This research is designed to identify the key areas of eWOM based on the Antecedents-Consequence-Intervention (ACI) framework. This paper is also aimed to analyze the current research status of each WOM area and critically review each area for developing future research directions.

616 articles were selected from 112 journals for in-depth review analysis. For the systematic review of articles, an ACI framework was adopted. This paper used systematic review analysis methodology to critically analyze important research studies in each area of the ACI framework with a set of research questions.

Results identify six significant areas of eWOM, i.e. WOM antecedents, outcomes, senders, receivers, eWOM platform and eWOM management representing the whole environment. The result highlights increasing research interest on mixed eWOM and rich eWOM content and market-level source credibility factors. Research also identifies research gaps based on the ACI framework.

Analyzing the recent trends in the eWOM environment with the SLR approach and linking these trends to the ACI framework with a future research agenda in the emerging market indicated a pioneering attempt in eWOM research.

Resilient firms are more likely to survive crisis. This paper aims to investigate the resilient behavior displayed by small and medium enterprise (SME) owners in the pandemic context and the sequence of antecedents leading to resilient behavior.

Seven SME owners, from different business sectors, were interviewed twice in 8 months, to assess their actions and underlying entrepreneurial resilience. A model was developed depicting the sequence of activities leading to entrepreneurial resiliency behavior. The study was conducted in the capital city of Odisha, an eastern Indian state.

The results indicate that entrepreneurial resiliency is manifested in various forms where the SME owners engage in bricolage. Resiliency has an inevitable time dimension, where SME owners estimate the period for which adversity is likely to persist. They focus on alternative action to demonstrate resiliency. It was also learnt that revenue management during a crisis requires entrepreneurial marketing with innovativeness, opportunity seeking and value creation to improve resiliency.

This research is important for policymakers who can strengthen resiliency through the support and provision of adequate information to SME owners. Educators can use the model for discussion and pedagogy. Finally, SME owners can evaluate their response behaviors to a crisis and draw insights.

The approach of the study was longitudinal and qualitative. This study contributes to the literature gap on resiliency in the context of emerging markets and SMEs.