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The purpose of this paper is to comprehend the nature of online reviews received on various social networking sites and internet-based platforms regrading organizational corporate social responsibility (CSR) initiatives.

Given the novelty of this field, a qualitative exploratory research study was carried out. For this research, 28 Indian CSR experts on online CSR reviews were interviewed with a semi-structured open-ended questionnaire for data collection. Thematic and relational content analysis was applied for data analysis. The data was analysed based upon the theoretical anchors of micro foundations approach, organizational egoism (reputational and economic) concept and organizational logic (instrumental and integrative) literature and stakeholder salience.

The study analysis indicated that online CSR reviews that organizations received on various social networking sites and internet-based platforms from different individual and institutional stakeholders were complaints, appreciations, observations and recommendations in nature. Online CSR reviews appreciated more of integrative organizational logic than instrumental organizational logic. CSR reviews present on online platforms valued organizational reputational egoism more than organizational economic egoism. The salience of stakeholders was getting redefines in Web 2.0 based online CSR reviews. Finally, micro foundations approach was becoming a more potent perspective in the CSR narrative.

This research study was anchored in the micro foundations approach of CSR (Hafenbrädl and Waeger, 2017). This study ascertained those individuals did matter in organizational CSR narrative (Maak et al., 2016). Furthermore, how firms were evaluated through online reviews based upon organizational egoism (reputational and economic) (Casali, 2011; Casali and Day, 2015) and organizational logic (instrumental and integrative) (Seele and Lock, 2015; Liu, 2013; Gao and Bansal, 2013; Bansal and Song, 2017) was studied. Finally, in the world of online reviews, the notion of salient stakeholders (Mitchell et al., 2011; Magness, 2008) was getting redefined, and this aspect was also covered in this research study.

Firms have been engaging in CSR initiatives towards provision of social benefits and community engagement. Regarding firm CSR initiatives, CSR managers traditionally used to receive feedback from the stakeholders based upon written and special surveys conducted post or during the late stages of CSR engagement. The advent and ubiquitous presence of digital mobile devices and Web 2.0-enabled internet connections altered the way firms received feedback. This was because increasingly online reviews were received from stakeholders on firm CSR web pages, social networking sites and other online spaces. Many of the online CSR reviews were regarding the compliments and achievements that the CSR initiatives had achieved. However, a significant portion of online CSR reviews were regarding the complaints regarding the CSR initiatives. Online CSR reviews received from an array of stakeholders are inputs for firm managers. Online CSR reviews are thus an asset for an organization. Managers need to develop capabilities towards applying this asset for the expressed purposed. These online CSR reviews could be used as inputs to draw new CSR initiatives, redefine extant CSR initiatives. Furthermore, these online CSR reviews could be used as inputs to alter the organizational resources, capabilities, competencies and process regarding CSR initiatives.

This was one of the first studies that integrated the theoretical aspects of salient stakeholders, organizational logic, organizational egoism through the lens of micro foundations approach in the context of organizational CSR initiatives. To the best of the author’s knowledge, this was indeed a novel contribution, as the same was explored and explicated based upon online CSR reviews on internet-based platforms.

Modern technologies are seen as an essential component of the fourth industrial revolution (industry 4.0) and their adoption is vital to transform the existing manufacturing system into industry 4.0-based manufacturing system. Therefore, the primary objective of this research explores the barriers of modern technology adoption and their mitigating solutions in order to align with Industry 4.0 objectives.

Barriers to adopting modern technologies and respective mitigating solutions are identified from the available literature. Further, these barriers are ranked with the help of expert opinions by using the BWM method appropriately. The identified solutions are ranked using the combined compromise solution (CoCoSo) method.

Several modern technologies and their capabilities are recognised to support the industry 4.0-based manufacturing systems. This study identifies 22 barriers to the effective adoption of modern technologies in manufacturing and 14 solutions to overcome these barriers. Change management, the high initial cost of technology and appropriate support infrastructure are the most significant barriers. The most prominent solutions to overcome the most considerable barriers are ‘supportive research, development and commercialisation environment’, ‘updated policy and effective implementation’ and ‘capacity building through training’ that are the top three solutions that need to be addressed.

The barriers and solutions of modern technology adoption are obtained through a comprehensive literature review, so there is a chance to ignore some significant barriers and their solutions. Furthermore, ranking barriers and solutions is done with expert opinion, which is not free from biases.

This identification and prioritisation of barriers will help managers to understand the barriers so they can better prepare themselves. Furthermore, the suggested solutions to overcome these barriers are helpful for the managers and could be strategically adopted through optimal resource utilisation.

This study proposes a framework to identify and analyse the significant barriers and solutions to adopting modern technologies in the manufacturing system. It might be helpful for manufacturing organisations that are willing to transform their manufacturing system into industry 4.0.

Grounded on the resource-based and dynamic capability views and the contingency theories, this study examines the direct and indirect effects of web technology training (WTT) and web-enabled transaction use (WTU) on business performance (BPE) through internal supply chain integration (ISCI) and supplier supply chain integration (SSCI).

Based on survey data collected from a sample of 175 respondents in the USA, the authors used structural equation modeling with AMOS 24.0 to test the measurement model for validity, reliability and the conceptual model for hypothesized structural relationships.

The results reveal that WTT significantly impacts WTU, which, in turn, has a significant direct relationship with BPE. Further, WTU indirectly affects BPE through SSCI. Additionally, ISCI has a significant direct effect on SSCI.

The findings support the relationship between WTT and BPE via WTU SCI. Managers are advised to develop ongoing capabilities in WTT to maximize the value of WTU to enhance the ISCI and SSCI operations, thus leading to improvements in BPE.

The research contributes to the supply chain literature by empirically demonstrating the usefulness of WTT in improving WTU use and BPE through effective ISCI and SSCI.

The use of technology in 4th industrial revolution is at its peak. Industries are trying to reduce the consumption of resources by effectively utilizing information and technology to connect different functioning agents of the manufacturing industry. Without digitization “Industry 4.0” will be a virtual reality. The present survey-based study explores the factual status of digital manufacturing in the Northern India.

After an extensive literature review, a questionnaire was designed to gather different viewpoints of Indian industrial practitioners. The first half contains questions related to north Indian demographic factors which may affect digitalization of India. The latter half includes the queries concerned with various operational factors (or drivers) driving the digital revolution without ignoring Indian constraints.

The focus of this survey was to understand the current level of digital revolution under the ongoing push by the Indian government focused upon digital movement. The analysis included non-parametric testing of the various demographic and functional factors impacting the digital echoes, specifically in Northern India. Findings such as technological upgradations were independent of type of industry, the turnover or the location. About 10 key operational factors were thoughtfully grouped into three major categories—internal Research and Development (R&D), the capability of the supply chain and the capacity to adapt to the market. These factors were then examined to understand how they contribute to digital manufacturing, utilizing an appropriate ordinal logistic regression. The resulting predictive analysis provides seldom-seen insights and valuable suggestions for the most effective deployment of digitalization in Indian industries.

The country-specific Industry 4.0 literature is quite limited. The survey mainly focuses on the National Capital Region. The number of demographic and functional factors can further be incorporated. Moreover, an addition of factors related to ecology, environment and society can make the study more insightful.

The present work provides valuable insights about the current status of digitization and expects to facilitate public or private policymakers to implement digital technologies in India with less efforts and the least resistance. It empowers India towards Industry 4.0 based tools and techniques and creates new socio-economic dimensions for the sustainable development.

The quantitative nature of the study and its statistical predictions (data-based) are novel. The clubbing of similar success factors to avoid inter-collinearity and complexity is seldom seen. The predictive analytics provided in this study is quite elusive as it provides directions with logic. It will help the Indian Government and industrial strategists to plan and perform their interventions accordingly.

The objective of this study is to examine current business and management research on “Industry 4.0 base technologies” and “business models” to shed light on this vast literature and to point out future research agenda.

The authors conducted a bibliometric analysis of scientific publications based on 482 documents collected from the Scopus database and a co-citation analysis to provide an overview of business model studies related to Industry 4.0 base technologies. After that a qualitative analysis of the articles was also conducted to identify research trends and trajectories.

The results reveal the existence of five research themes: smart products (cluster 1); business model innovation (cluster 2); technological platforms (cluster 3); value creation and appropriation (cluster 4); and digital business models (cluster 5). A qualitative analysis of the articles was also conducted to identify research trends and trajectories.

First, the dataset was collected through Scopus. The authors are aware that other databases, such as Web of Science, can be used to deepen the focus of quantitative bibliometric analysis. Second, the authors based this analysis on the Industry 4.0 base technologies identified by Frank et al. (2019). The authors recognize that Industry 4.0 comprises other technologies beyond IoT, cloud computing, big data and analytics.

Drawing on these analyses, the authors submit a useful baseline for developing Industry 4.0 base technologies and considering their implications for business models.

In this paper, the authors focus their attention on the relationship between technologies underlying the fourth industrial revolution, identified by Frank et al. (2019), and the business model, with a particular focus on the developments that have occurred over the last decade and the authors performed a bibliometric analysis to consider all the burgeoning literature on the topic.

This research paper aims to analyze the scientific and grey literature on Quality 4.0 and zero-defect manufacturing (ZDM) frameworks to develop an integrated quality 4.0 framework (IQ4.0F) for quality improvement (QI) based on Six Sigma and machine learning (ML) techniques towards ZDM. The IQ4.0F aims to contribute to the advancement of defect prediction approaches in diverse manufacturing processes. Furthermore, the work enables a comprehensive analysis of process variables influencing product quality with emphasis on the use of supervised and unsupervised ML techniques in Six Sigma’s DMAIC (Define, Measure, Analyze, Improve and Control) cycle stage of “Analyze.”

The research methodology employed a systematic literature review (SLR) based on PRISMA guidelines to develop the integrated framework, followed by a real industrial case study set in the automotive industry to fulfill the objectives of verifying and validating the proposed IQ4.0F with primary data.

This research work demonstrates the value of a “stepwise framework” to facilitate a shift from conventional quality management systems (QMSs) to QMSs 4.0. It uses the IDEF0 modeling methodology and Six Sigma’s DMAIC cycle to structure the steps to be followed to adopt the Quality 4.0 paradigm for QI. It also proves the worth of integrating Six Sigma and ML techniques into the “Analyze” stage of the DMAIC cycle for improving defect prediction in manufacturing processes and supporting problem-solving activities for quality managers.

This research paper introduces a first-of-its-kind Quality 4.0 framework – the IQ4.0F. Each step of the IQ4.0F was verified and validated in an original industrial case study set in the automotive industry. It is the first Quality 4.0 framework, according to the SLR conducted, to utilize the principal component analysis technique as a substitute for “Screening Design” in the Design of Experiments phase and K-means clustering technique for multivariable analysis, identifying process parameters that significantly impact product quality. The proposed IQ4.0F not only empowers decision-makers with the knowledge to launch a Quality 4.0 initiative but also provides quality managers with a systematic problem-solving methodology for quality improvement.

The purpose of this study was to ascertain how real options investment perspective could be applied towards monetization of customer futures through the deployment of machine learning (ML) and artificial intelligence (AI)-based persuasive technologies.

The authors embarked on a theoretical treatise as advocated by scholars (Cornelissen, 2019; Barney, 2018; Cornelissen, 2017; Smithey Fulmer, 2012; Bacharach, 1989; Whetten, 1989; Weick,1989). Towards this end, theoretical argumentative logic was incrementally used to build an integrated perspective on the deployment of learning and AI-based persuasive technologies. This was carried out with strategic real options investment perspective to secure customer futures on m-commerce apps and e-commerce sites.

M-commerce apps and e-commerce sites have been deploying ML and AI-based tools (referred to as persuasive technologies), to nudge customers for increased and quicker purchase. The primary objective was to increase engagement time of customers (at an individual level), grow the number of customers (at market level) and increase firm revenue (at an organizational level). The deployment of any persuasive technology entailed increased investment (cash outflow) but was also expected to increase the level of revenue and margin (cash inflow). Given the dynamics of market and the emergent nature of persuasive technologies, ascertaining favourable cash flow was challenging. Real options strategy provided a robust theoretical perspective to time the persuasive technology-related investment in stages. This helped managers to be on time with loading customer purchase with increased temporal immediacy. A real options investment space involving six spaces has also been developed in this conceptual work. These were Never Invest, Immediately Investment, Present-day Investment Possibility, Possibly Invest Later, Invest Probably Later and Possibly Never Invest.

The foundations of this study domain encompassed work done by an eclectic mix of scholars like from technology management (Siggelkow and Terwiesch, 2019a; Porter and Heppelmann, 2014), real options (Trigeorgis and Reuer, 2017; Luehrman, 1998a, 1998b), marketing intelligence and planning (Appel et al., 2020; Thaichon et al., 2019; Thaichon et al., 2020; Ye et al., 2019) and strategy from a demand positioning school of thought (Adner and Zemsky, 2006).

The findings would help managers to comprehend what level of investments need to be done in a staggered manner. The phased way of investing towards the deployment of ML and AI-based persuasive technologies would enable better monetization of customer futures. This would aid marketing managers for increased customer engagement at the individual level, fast monetization of customer futures and increased number of customers and consumption on m-commerce apps and e-commerce sites.

This was one of the first studies to apply real options investment perspective towards the deployment of ML and AI-based persuasive technologies for monetizing customer futures.

It is crucial for the Indian micro, small and medium enterprises (MSMEs) to implement a few of the most important Industry 4.0 (I4.0) technologies and reap maximum benefits of sustainability. This paper aims to prioritize I4.0 technologies that can help achieve the sustainable operations and sustainable industrial marketing performance of Indian manufacturing MSMEs.

I4.0-based sustainability model was developed. The model was analyzed using data collected from MSMEs by deploying analytic hierarchy process and utility-function-based goal programming. To have a better understanding, interviews were conducted.

Predictive analytics, machine learning and real-time computing were found to be the most important I4.0 technologies for sustainable performance. Sensitivity analysis further confirmed the robustness of the results. Business-to-business sustainable marketing is prioritized as per the sustainability need of operations of industrial MSME buyers.

This study uniquely integrates literature and practitioners’ insights to explore I4.0’s role in MSMEs sustainability in emerging economies. It fills a research gap by aligning sustainability goals of industrial buyers with suppliers’ marketing strategies. Additionally, it offers practical recommendations for implementing technologies in MSMEs, contributing to both academia and industry practices.

This paper proposes strategies for adopting Industry 4.0 in achieving sustainable manufacturing, by overcoming barriers in the Sri Lankan manufacturing sector.

A conceptual model of sustainable manufacturing and Industry 4.0 was proposed based on a comprehensive literature review and validated through experts' inputs. The model was illustrated using three case studies to assess the relationships between sustainable manufacturing and Industry 4.0 in the Sri Lankan manufacturing context. Furthermore, possible strategies were proposed to overcome current barriers identified from case studies.

The case studies showcase that there is a considerable gap in Industry 4.0-enabled sustainable manufacturing in the Sri Lankan manufacturing sector due to several barriers. Thus, experts' knowledge-based strategies to overcome those barriers are proposed.

The conceptual model provides a holistic view of maturity levels of sustainable manufacturing measures directly connected with Industry 4.0 technologies. The study was limited to investigating the application of Industry 4.0 for sustainable manufacturing in leading apparel manufacturing organisations in Sri Lanka.

The conceptual model can be used as a framework to guide practitioners in implementing Industry 4.0-enabled sustainable manufacturing. The proposed strategies in addressing barriers to Industry 4.0 adoption towards sustainable manufacturing can be directly applied to achieving better sustainable manufacturing performance.

This study is an informative guide to encourage the Sri Lankan manufacturing industry to adopt Industry 4.0 technologies in achieving sustainable manufacturing, using the knowledge of relationships between Industry 4.0 and three dimensions of sustainable manufacturing, possible barriers and strategies.