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Purpose: Nowadays, many terms like computer vision, deep learning, and machine learning have all been made possible by recent artificial intelligence (AI) advances. As new types of employment have risen significantly, there has been significant growth in adopting AI technology in enterprises. Despite the anticipated benefits of AI adoption, many businesses are still struggling to make progress. This research article focuses on the influence of elements affecting the acceptance procedure of AI in organisations.

Design/Methodology/Approach: To achieve this objective, propose a hierarchical paradigm for the same by developing an Interpretive Structural Modelling (ISM). This paper reveals the barriers obstructing AI adoption in organisations and reflects the contextual association and interaction amongst those barriers by emerging a categorised model using the ISM approach. In the next step, cross-impact matrix multiplication is applied for classification analysis to find dependent, independent and linkages.

Findings: As India is now focusing on the implementation of AI adoption, therefore, it is essential to identify these barriers to AI to conceptualise it systematically. These findings can play a significant role in identifying essential points that affect AI adoption in organisations. Results show that low regulations are the most critical factor and functional as the root cause and further lack of IT infrastructure is the barrier. These two factors require the most attention by the government of India to improve AI adoption.

Implications: This study may be utilised by organisations, academic institutions, Universities, and research scholars to fill the academic gap and faster implementation of AI.

The purpose of this chapter is to identify and analyze various critical success factors (CSFs) that can facilitate retailing business in Thailand. This chapter further aims to understand the mutual interactions among these CSFs through identification of the hierarchical relationships among them. A framework for Thai retailers has been developed, wherein the hierarchical interrelationships between identified CSFs have been presented and interpreted using total interpretive structural modeling (TISM). Cross-impact matrix multiplication applied to classification analysis has been further employed to identify the driving power as well as dependence power of these CSFs. In the present research, 15 CSFs have been identified through literature review and expert opinions. The methodology employed in this study provides a mechanism to conduct an exploratory study by identifying the factors and analyzing their interactions through the development of a hierarchical framework. The proposed framework developed through qualitative modeling is an effort to understand relevant factors that can apply to the Thai retailers. This study makes a significant contribution in the literature of retailing business, which captures the perspective of different customers.

This chapter introduces four research methods that are not covered in the previous chapters. They are (1) non-parametric statistics, (2) interpretive structural modeling, (3) analytic hierarchy process, and (4) data envelopment analysis. The methods are discussed with examples. The discussion, however, is introductory; so we urge the reader to go through the pertinent references for details.

In recent years, due to fast growth of Kabul city in Afghanistan, newest construction has been taking place in unplanned ways and entailed illegal squatting on land and mountains. Such unplanned urban expansion, without any type of urban infrastructure and insufficient drainage systems, has created many problems including an increasing number of urban floods. Recent reports show that the number of female victims is higher than that of males affected by floods. First, this chapter highlights the country overview of the disaster and vulnerability, and then particularly focus on the vulnerability factors of urban women who are affected by floods and living in Kabul city. Data for this study were obtained through focus group discussions with urban women, and men and face-to-face interviews with governmental and non-governmental organizations (GOs-NGOs) at the local as well as national levels in Afghanistan. Interpretive Structural Modelling (ISM) was used to map the relationship among factors, and to stratify factors according to their importance. Findings show that the lack of education on disaster management and the lack of protective measures play an important role in increasing women’s vulnerability during disasters. Furthermore, the study finds that cultural issues represent a dominant vulnerability factor which affect women. The comparative results show that the women affected by the cultural norms during the flood are less important than the post-disaster. The study also found that the perception regarding these cultural norms and how they affect women’s behaviour during disasters differs between men and women. This chapter concluded some policy recommendations towards resilient livelihoods.

This study aims to identify the factors and propose a conceptual framework for the civil aviation industry from the sustainability perspective with the participation of international entrepreneurs. Based on the results of this study, international decision-makers and entrepreneurs in the civil aviation transportation industry will better understand their decision-making processes. A combination of interpretive structural modelling (ISM) and matrix-based multiplication applied to a classification (MICMAC) was used to classify practical factors to depict a conceptual model based on their level and classification in the sustainable supply chain (SSC) of the civil aviation transportation industry. In this study, special attention has been paid to the issue of sustainability as an essential mechanism for developing international entrepreneurship in the civil aviation transportation industry. The factor of flexibility in service production was identified as the driver factor; the factors of organisational commitment to a SSC were found to have the highest driver-dependent power that can attract international entrepreneurs in this field.

This study deals with the examination, classification and ranking of the food industry supply chain in Mazandaran Free Economic Zone from a sustainability perspective and its effect on international entrepreneurship. The findings can help international decision-makers and entrepreneurs better understand their decision-making processes. Interpretive structural modelling (ISM) and Matrix-based Multiplication Applied to Classification (MICMAC) methods is an export-oriented method. The indicators are determined based on the definitive opinion of experts. Indicators in this research were selected using fuzzy Delphi with 99% accuracy. A combination of ISM–MICMAC methods were used based on sustainable facts in the food supply chain. The developed classify the factors practical on the sustainable supply chain. The findings showed that minimising the total cost, improvement of health and safety, environmentally friendly packaging, use of environmentally friendly materials and minimising the use of synthetic fertilisers were among the linkage factors. Factors that reduce energy costs, the possibility of immediate customer response and social services were among the dependent factors. Since free economic zones have been established to attract international investment, exploit new technologies, create new job opportunities and increase export capacity, the focus on reducing costs and the ability to respond immediately to customers and providing social services can result in the creation of a suitable business position for international investment and attracting international entrepreneurs.

This chapter aims to identify, analyse, classify and rank the sustainability indices and internationalisation challenges of the footwear industry in the emerging economy of Iran. This would provide deeper decision-making insights into Iranian footwear businesses. First, a list of sustainability indices and internationalisation challenges was obtained by reviewing the literature. Then, a combination of multi-criteria decision-making (MCDM) approaches was implemented. The initial sustainability indices and internationalisation challenges were screened using the fuzzy Delphi method, keeping a total of 14 criteria. The best–worst method (BWM) was employed to weigh and rank the criteria. The interpretive structural modelling (ISM) technique and cross-impact matrix applied in MICMAC were employed to visualise the conceptual model based on the levels and classification of the important criteria for the internationalisation of the Iranian footwear industry. The 14 criteria were demonstrated to be important in internationalisation. The most critical sustainability indices were reducing hazardous substances in leather tanning and labour education and training. In contrast, exchange rate instability in Iran’s economy and strict chemical regulations for clothing and footwear were found to be the most important internationalisation challenges. Hence, these criteria should be considered in the internationalisation strategies of the Iranian footwear industry. A combined multilayer sustainable decision-making approach was used to analyse the Iranian footwear industry’s essential sustainability indices and internationalisation challenges. Furthermore, implications and insights are offered to footwear businesses for future decision-making.

This chapter assists in Iran’s start-ups swift internationalisation from the onset. Indeed, it sheds in-depth qualitative and quantitative insights into analysing the propelling factors towards entrepreneurial internationalisation. To accomplish this feat, a mixed method of Systematic Literature Review (SLR), Fuzzy-Delphi (FD) and Fuzzy-DEMATEL (Decision Making Trial and Evaluation Laboratory) – ISM (Interpretive Structural Modelling) – MICMAC (Matrix-based Multiplication Applied to a Classification) (FDIM), along with a multi-scenario analysis have innovatively been applied. As a result, entrepreneur characteristics and an accessible qualified workforce, even in foreign countries, are the most prominent drivers. Most probably, the institutional voids, interconnected benchmarking and the advent of new disruptive technologies form the independent factors which can sharply influence the whole system, particularly the entrepreneur characteristics as a dependent one. Moreover, social media, customer orientation and the domestic market cover autonomous drivers, which can moderately be affected or influence the abovementioned factors.