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Organizations are fast adopting new technologies such as automation, analytics and artificial intelligence, collectively called intelligent automation, to drive digital transformation. When adopting intelligent automation, there is a need to understand the success factors of these new technologies and adapt agile software development (ASD) practices to meet customer expectations. The purpose of this paper is to explore the success factors of intelligent automation and create a framework for managers and practitioners to meet dynamic business demands. Total interpretive structural modeling (TISM) framework is a suitable approach to integrate quantitative measurement with qualitative semi-structured interviews capturing the context of the individual organization environment.

This paper identified agility factors and their interrelationships using a TISM framework. TISM results were validated using a one-tailed t-test to confirm the interrelationships between factors. Furthermore, the agility index of a case project organization was assessed using a graph-theoretic approach (GTA) to identify both the triggering factors for agility success and improvement proposals.

Results showed that leadership vision, organization structure and program methodology were driving factors. The TISM model was validated statistically and the agility index of the intelligent automation case project organization was calculated to be79.5%. Here, a GTA was applied and the triggering factors for improvement of the agility index were identified.

The limitations of the study are described along with the opportunities for future research as the field evolves through the rapid innovation of technology and products.

The increasing role of digital transformation in enterprise strategy and operations requires practitioners to understand how ASD practices must be planned, measured and/or improved over time through the implementation of automation, analytics and artificial intelligence programs. The TISM digraph provides a framework of hierarchical structure to organize the influencing factors, which assists in achieving organizational goals. This study highlights the driving factors which contribute to the success of intelligent automation projects and project organizations.

This is a first attempt to analyze the interrelationships among agility factors in intelligent automation projects (IAP) using TISM and the assessment of the agility index of a case IAP organization using a GTA.

The purpose of this paper is to formulate frameworks for the drivers and barriers of integrated sustainable solid waste management (ISSWM) with reference to conditions prevailing in India.

A multi-phased approach was adopted in this paper to come up with the conceptual framework of the drivers and barriers of ISSWM. In the first phase, drivers and barriers of ISSWM were identified based on a systematic literature review process. In the second phase, 25 experts having 15 plus years of experience in the field of sustainable development and environmental management were consulted to get their opinion. Validation and understanding of the interrelationship among the selected drivers and barriers were done based on the insights from expert interviews. And in the final phase, structural self-interaction matrix and transitive links are defined based on the expert opinion to come up with the theoretical frameworks of drivers and barriers of ISSWM.

Findings reveal the importance to have a system view point approach by giving equal importance to social, environmental and economic pillars of sustainability along with the technology component to effectively and sustainably manage the solid waste disposal. Institutional effectiveness and the robust policy and frameworks are the two variables found to have the highest driving power. Poor social values and ethics, huge population and illiteracy are the three most critical barriers faced by developing nations in achieving the sustainability practices in the solid waste management. The proposed frameworks of drivers and barriers of ISSWM will definitely help policy makers to effectively manage the sustainable waste management practices for developing economies by focusing on the key variables listed out.

One of the limitations is in the use of very limited sample size in the study. Another limitation is that total interpretive structural modeling fails to come up with the relative weightings of drivers and barriers used in the study. These limitations can be overcome by extending the research by using a semi-structured questionnaire survey with higher sample size for the empirical validation of the model.

This research will help to clearly understand the framework of drivers and barriers of variables and their hierarchical level based on the driving power and dependence. Since such articles focusing on the conceptual frameworks of drivers and barriers of ISSWM are found to be very scant, this paper will equally help academicians and waste management professionals to understand the concepts deeply, by getting answers to the fundamental questions of “what,” “why” and “how.” Developed framework of drivers explicitly shows the need to attain financial stability through the commercialization of the waste management initiatives, which will help to reduce burden on various governmental institutions. Commercialization opportunities will also help to have more successful start-up ventures in solid waste management domain that can provide improved employment opportunities and hygiene environment in the developing nations like India.

Based on the authors’ best knowledge, there is hardly any article that explicitly explains the conceptual frameworks of the drivers and barriers of ISSWM by considering the conditions prevailing in developing countries like India. And thus, this can be considered as one of the unique research attempts to build a clear conceptual framework of ISSWM. The study contributes significantly to the existing literature body by clearly interpreting the interrelationships and the driving power and dependence of variables of ISSWM.

The COVID-19 crisis has created enormous strain in global supply chains. The disruption has caused severe shortages of critical items, including personal protective equipment (e.g. face masks), ventilators and diagnostics. The failure of the industry to meet the sudden demand for these necessary items has caused a severe humanitarian crisis. These situations, resulting from the COVID-19, crisis have led to the informal growth of frugal innovation in sustainable global supply chains. This paper aims to provide a detailed overview of drivers of frugal-oriented sustainable global supply chains, following lessons acquired from emerging countries’ attempts to deal with the COVID-19 pandemic.

The authors used a focused group approach to identify the drivers and this paper further validated them using existing literature published in international peer-reviewed journals and reports. The authors adopted total interpretive structural modeling (TISM) to analyze the complex relationships among identified drivers.

The authors present a theoretical framework to explain how the drivers are interlinked. This paper has developed the framework through a synthesis of the TISM modeling and Matrice d’impacts croisés multiplication appliquée á un classment analysis. This paper observed that government financial support, policies and regulations, under the mediating effect of leadership and the moderating effect of national culture and international rules and regulations, has a significant effect on the adoption of emerging technology, volunteering initiatives and values and ethics. Further, emerging technology, volunteering initiative and values and ethics have a significant effect on supply chain talent and frugal engineering. These results provide some useful theoretical insights that may help in further investigating the role of frugal innovations in other contexts.

The authors find that outcomes of the methodical contributions and the resulting managerial insights can be categorized into four levels. Industry and researchers alike can use the study to develop the decision-support systems guiding frugal-oriented sustainable global supply chains amid the COVID-19 pandemic and in recovering them thereafter. Suggestions for future research directions are offered and discussed.

Over the last 2 decades, supply chain sustainability research has become a highly dynamic and fruitful study area. This field has garnered significant attention due to its potential to reshape decision-making processes within supply chains. At the same time, the practical side of supply chain operations remains intensely competitive in today’s business landscape. Furthermore, the current academic research aims to outline effective strategies for achieving sustainability across supply chains, particularly in the manufacturing sector. In response to these challenges, this research has conducted an integrated multi-criteria decision-making approach to evaluate sustainable supply chain performance from the triple bottom line perspective, including financial, environmental, and social performance.

The initial stage involves selecting the crucial criteria (short-term and long-term) and alternatives for sustainable supply chain performance (SSCP) from experts and conducting an in-depth literature review. Initially, there were 17 criteria, but after a pilot test with co-authors and online discussions with experts, the number of criteria was subsequently reduced to 9. In the second phase, the Best-Worst Method (BWM) was applied to rank and prioritize the criteria. The third and final stage examined the causal relationship between the identified criteria, utilizing the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique.

Based on BWM analysis results, the top three criteria in terms of prominence are: (1) return on investment (ROI), (2) product quality, and (3) manufacturing lead time. Out of the three alternatives, financial performance (FP) is the most crucial dimension for SSCP, followed by environmental performance (ENP) and social performance (SP). On the other hand, the DEMATEL approach showed that work health and safety (short-term criterion), asset utilization (long-term criterion), energy consumption (long-term criterion), waste disposal (long-term criterion), manufacturing lead time (short-term criterion), and on-time delivery (short-term criterion) are categorized within the cause group, while criteria such as return on investment (ROI) (long-term criterion), customer-service level (short-term criterion), and product quality (long-term criterion) fall into the effect group.

The proposed study has certain drawbacks that pave the way for future research directions. First, it is worth noting the need for a larger sample size to ensure the reliability of results, the potential inclusion of additional criteria to enhance the assessment of sustainability performance, and the consideration of a qualitative approach to gain deeper insights into the outcomes. In addition, fuzziness in qualitative subjective perception could be imperative when collecting data to ensure its reliability, as translating experts’ perceptions into exact numerical values can be challenging because human perceptions often carry elements of uncertainty or vagueness. Therefore, fuzzy integrated MCDM frameworks are better suited for future research to handle the uncertainties involved in human perceptions, making it a more appropriate approach for decision-making in scenarios where traditional MCDM methods may prove insufficient.

The proposed framework will enable decision-makers to gain deeper insights into how various decision criteria impact SSCP, thus providing a comprehensive evaluation of SSCP that considers multiple dimensions, such as financial, environmental, and social performance within the manufacturing sector.

The proposed study is the first empirical study to integrate both BWM and DEMATEL approaches to evaluate sustainable supply chain performance in the manufacturing context.

Humanitarian services usually perform in the face of uncertainty in which mobilization of resources in an efficient and effective manner is a big challenge. Sharing timely and correct information among logistics partners and workers is a key to drive rapid response logistics effectively. The purpose of this paper is to understand how coordinated effort effects resources management (RM).

This study uses quantitative research methodology and collected data from 82 humanitarian workers dealing with logistical activities from a densely populated city of Pakistan. Data were then statistically analyzed through partial least squares–structural equation modeling.

The results suggest that the success of humanitarian supply network depends upon the level of trust among the partners, which accelerates commitment through strong coordination. Information sharing reduces behavioral uncertainty and enhances swift trust (ST). ST then helps to improve coordination and commitment from all stakeholders in order to manage resources to lead effective relief operations.

The study guides the practitioners and relief operations’ policy makers to lay emphasis on distributing right and timely information flow among the partners, which can lead to effective, efficient and swift humanitarian relief operations.

This study on RM during humanitarian logistics is well timed in the context of developing country with high uncertain events, improper infrastructure and very limited resources.

Kids get exposed to advertising on social media platforms when they visit them to perform various goals. The purpose of this study is to find out the factors which affect kids' behaviour when the kids encounter advertising on social media and also to establish causal relationships amongst the factors of social media advertising (SMA).

A total of 11 factors of SMA have been identified with the help of experts and the causal relationships amongst the SMA factors have been constructed by the implementation of decision-making trail and laboratory evaluation (DEMATEL). Based on the established relationships, a causal diagram has been also developed to understand the structural nature of interdependence amongst the factors.

DEMATEL technique is based on logical steps, which have assisted in categorising the identified factors into two groups: cause group and effect group. Cause group factors are the reasons for the effect group factors to occur. Customisation, entertainment, information and interactivity have been observed as cause factors whereas, relevance, engagement with SMA, purchase intention, product involvement, advertising value, attitude towards SMA and irritation have been observed as effect factors. Product involvement is found to have the highest level of interaction with all other factors. Information and interactivity are observed to influence all other factors.

Kids possess a limited understanding of the selling intent of advertisers which makes kids vulnerable to advertising. This study supports that the content of the advertisement should be kept in accordance with the need of kids and also suggests that marketers should emphasise cause group factors which derive subsequent consequences on effect group factors. The foremost limitation of this study lies in the process of identifying the factors through expert opinions. The sets of contextual relationships may vary when different experts are considered.

This study strives to identify the factors which affect kids' understanding of SMA and also establishes causal relationships amongst them. This kind of study is unique in state of the art and to the authors' knowledge no significant research has been conducted in India which involves establishment of inter-relationships amongst SMA factors that affect kids' behaviour.

Nowadays, a prominent research area is the development of competitive advantages in companies, due to their environmental commitment and orientation. Based on resource-based view (RBV) and institutional theory (InT), this paper aims to investigate the influence of internal and external orientation on businesses' sustainable performance while considering the effect of sustainable supply chain management (SSCM) practices.

Data from 351 manufacturing companies in the Kingdom of Saudi Arabia have been collected and analysed through structural equation modelling (SEM) using the partial least squares (PLS) method.

The results indicated that both internal and external environmental orientation have important effects on SSCM practices, which in turn have a considerable beneficial effect on environmental, social and economic performance.

Although SSCM is constantly gaining ground in the literature, most SSCM research and models examine its effects, antecedents or motivation, mainly adopting a qualitative approach. Research on the topic adopting a large-scale empirical approach is still limited. In this context, this study contributes to the SSCM management literature by exploring the role of environmental orientation in facilitating the adoption of SSCM practices and improving companies' performance.

The coronavirus disease 2019 (COVID-19) pandemic created heavy pressure on firms, by increasing the challenges and disruptions that they have to deal with on being sustainable. For this purpose, it is aimed to reveal the role of the smart circular supply chain (SCSC) and its enablers towards achieving Sustainable Development Goals (SDGs) for post-pandemic preparedness.

Total interpretive structural modelling and Matrice d'Impacts Croises Multipication Applique' a un Classement (MICMAC) have been applied to analyse the SCSC enablers which are supported by the natural-based resource view in Turkey's food industry. In this context, industry experts working in the food supply chain (meat sector) and academics came together to interpret the result and discuss the enablers that the supply chain experienced during the pandemic for creating a realistic framework for post-pandemic preparedness.

The results of this study show that “governmental support” and “top management involvement” are the enablers that have the most driving power on other enablers, however, none of them depend on any other enablers.

The identification of the impact and role of enablers in achieving SDGs by combining smart and circular capabilities in the supply chain for the post-pandemic.

The purpose of this paper is to differentiate the empowering influences of critical enablers of supply chain management (SCM) along with their interrelationships. These empowering enablers are significant, as they encourage productive execution to improve organizational performance and stakeholder's satisfaction.

From the literature review, incidence of a number of SCM enablers were found and they were subjected to critical scrutiny by a considerable number of experts engaged in SCM research and application to identify significant and applicable empowering enablers by grounded interactions. By using Impact Matrix Cross-Reference Multiplication Applied to a Classification analysis, the driving and dependence power were analyzed and the empowering enablers were ordered. This was pursued by building up a structural model of the empowering enablers using interpretive structure modeling, followed with measuring cause–effect relationship using decision-making trial and evaluation laboratory (DEMATEL).

Among these identified enablers of SCM, operational performance, green SCM, employee empowerment and motivation and strategic association came out to be strategic enablers.

The findings may help the practicing professionals to develop clarity in understanding of these essential enablers and their contextual as well as cause–effect relationship in SCM. The practicing professionals need to focus on all these enablers during implementation of SCM for enhancing the organizational performance and stake holders' satisfaction.

This study is of practical utility in real-life implementation of SCM. The algorithm used in applying the multi-criteria decision-making approach is very user-friendly, and the application of DEMATEL is an innovation compared to previous research. Further, the findings can be used as a benchmark for improving the performance of SCM by considering the cause–effect relationship.

The purpose of this paper is to analyze research methodologies and publication trends across geographical regions in the field of supply chain innovation (SCI) and provide a discussion of future research in the SCI.

Using a content analysis approach, this paper investigates 26 years of SCI research based on a sample of 473 journal articles published in 77 peer-reviewed international journals.

There has been an increasing focus on empirical quantitative research design as compared to empirical qualitative, conceptual quantitative and conceptual qualitative designs in the field of SCI. Continued research interest in SCI from all parts of the world including North America, Europe and Asia illustrates the importance of SCI in the broader field of management.

The inclusion of a large number of journals provides greater confidence in the identified trends. However, as the top-tier journals publish only the most rigorous studies, considering all journals as equally weighted will give rise to a mixed pool of studies. Identifying trends from this mixed pool may provide more comprehensiveness at the cost of inclusion of non-core journals of the field.

The current study builds a holistic view of the methodological progress made so far in the field of SCI.