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The purpose of this study is to identify and prioritize the critical success factors (CSFs) of knowledge management (KM) implementation through a novel hybrid model, namely, Fuzzy Delphi method (FDM), interpretive structural modeling (ISM) and revised Simos, which is one of group decision-making (GDM) approaches.

The CSFs of KM implementation were identified through a systematic literature review. FDM was adopted to determine the CSFs in the Iranian oil industry. Then, a novel hybrid model consisting of ISM and revised Simos techniques were used to classify and prioritize the CSFs.

The obtained results suggest that there are 13 CSFs of KM implementation. The result of ISM shows that the CSFs of KM implementation were classified into five levels. The result of revised Simos reveals that the “human resources management” obtained the highest priority and “leadership commitment and support” and “intellectual capital” ranked second and third, respectively.

As this research was performed in the Iranian oil industry, caution should be taken regarding the generalizability of the obtained results.

The top managers of the surveyed companies could get acquainted with CSFs of KM implementation in their organization and use a GDM technique that has various advantages to solve the relevant problems.

This paper provides a twofold contribution to expand KM and GDM literature and to the best knowledge of the authors, it is a novel hybrid GDM model of its kind.

The main purpose of this study is to assess the influence of business analytics (BA) on supply chain ambidexterity (SCA) and market learning (ML) in the context of Iran as a developing country.

The study population encompasses a range of key positions such as senior managers, supply chain managers, senior IT managers and senior marketing and marketing research managers in Iran. Through a survey, a questionnaire was designed to gather data from these individuals. The data collected from a total of 214 participants underwent rigorous analysis using structural equation modeling.

Findings revealed BA has a positive influence on SCA and ML. Furthermore, the study found that distinct facets of ML, namely, exploratory and exploitative learning, exerted a positive influence on SCA. Additionally, the investigation uncovered that the mechanisms of exploratory ML and exploitative ML play a partially mediating role in the relationship between BA and SCA.

It is prudent to acknowledge that the study’s sampled entities were exclusively Iranian companies, potentially curtailing the extent of generalizability of our findings.

This research contributes valuable theoretical insights and practical implications to policymakers and top managers of organizations, particularly the surveyed organizations to formulate and implement an appropriate strategy to avail of BA techniques toward enhancing SCA. Also, this study provides significant insights into the determinants of SCA and demonstrates how organizations can leverage data analytics and ML to attain sustained growth and ambidexterity within the supply chain context.

In the digital age, emerging technologies have affected every industry. Information and communications technology and digital technologies have transformed traditional supply chains into smart and more resilient ones, enabling effective management of challenges. Given the importance of the two topics, namely sustainable supply chain management and Industry 4.0 in supply chain management, on the one hand, and the dearth of theoretical research performed in this area on the other, this study aims to propose a conceptual model on a sustainable digital supply chain management in manufacturing companies.

This study utilized a qualitative approach. First, an in-depth review of the relevant literature was done. Then, following a multi-grounded theory methodology, relevant data were gathered by reviewing 92 papers and conducting nine semi-structured interviews with industry experts. These data were analyzed using the MAXQDA software.

A total of 41 concepts, ten sub-components and three main components (dimensions) were extracted, and the proposed conceptual model was presented. Finally, based on this conceptual model, three propositions were suggested.

Considering that the present study was performed in the context of Iranian manufacturing companies, caution should be exercised in relation to the generalizability of the obtained results. Also, due to the problems in the digital technology infrastructure and the limited use of these technologies by manufacturing companies (emphasized by the interviewees), this study focused on the theoretical dimension of using digital technologies by these companies.

The proposed comprehensive model can help academicians as well as practitioners to focus better and explore the variables and constructs of the model, paving the way toward successful implementation of digital technologies in the manufacturing supply chain.

To the best knowledge of the authors, this study is among the first of its kind which presents a holistic and comprehensive digital supply chain model aimed at guiding companies to consider sustainability from all the main dimensions and their relevant indicators.

This research investigates the impact of business analytics (BA) on corporate entrepreneurship (CE) and open innovation (OI), considering the moderated mediation analysis in the context of Iran as a developing country. The study was conducted in various industries, including food, chemicals, agriculture, automobile, and service industries, with 207 observations.

Through an in-depth review of the extant literature a conceptual model was developed and the proposed hypotheses were tested using Structural Equation Modeling technique (PLS-SEM).

The results indicate that business analytics has significant effects on corporate entrepreneurship and open innovation. Open innovation has a significant effect on corporate entrepreneurship, with open innovation serving as a suitable mediator. Furthermore, the moderated mediation analysis shows the positive impact of Business Analytics on Open Innovation-Corporate Entrepreneurship relationship.

As this study was conducted in Iran, one of the main limitations can be attributed to the specific characteristics of the country which may affect how and how much the variables influence each other.

The study highlights the importance of promoting Open Innovation in organizations and utilizing Business Analytics to make strategic decisions and foster innovation in entrepreneurial activities.

This study fills the gap in the literature by exploring how BA contributes to corporate entrepreneurship of the Iranian organizations in various industries, given open innovation as a mediator under dynamic market conditions.

To gain and differentiate competitive advantage, the sustainable service quality is a determining factor that railway companies can use. The purpose of this study is to identify both the importance and performance of rail transportation service quality factors in a case study as well as determine the most influential quality features.

A comprehensive approach namely importance–performance analysis (IPA) technique and decision-making trail and evaluation laboratory (DEMATEL), and interpretive structural modeling (ISM) and Matriced’ Impacts Croisés Multiplication Appliquée á un Classement (MICMAC) techniques was utilized.

The relative position of each attribute is specified on the IPA matrix proposing four strategies of concentrate here, keep up the good work, low priority and possible overkill. This study reveals that attributes of “the company cares about having a good society” are the most influential factor, and “having good business relations with shareholders” is the most permeable factor. Actually, consumers pay attention to how companies act toward society and maintain communication with shareholders. Through ISM technique and by summing the row and column of the consistency matrix, the attributes were partitioned into four levels. Also, MICMAC analysis identified the four clusters of linkage, independent, autonomous and dependent status of the attributes in terms of the driving power and dependence power.

Due to the nature of single case study methodology, caution should be taken into consideration regarding the generazability of the obtained results.

The hybrid DEMATEL-ISM technique is used to analyze service quality factors in Iran’s transportation industry, which can be utilized in other industries as well as other countries.