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This paper aims to present a review of small and medium-sized enterprise (SME) literature on the adoption of technology for marketing with the objective the knowledge trajectory from SMEs to tourism SMEs (TSMEs) and presents a research agenda for the adoption of digital marketing among TSMEs.

The quantitative literature review method is adopted to analyze 50 articles published in high-ranking journals from 2011–2021. The selected papers were reviewed to quantitatively present the popular theoretical frameworks, constructs and research methods used for the adoption of digital marketing among SMEs and to present a future research agenda in the context of TSMEs.

The findings present a review of theoretical approaches, research design, methods, and models used by researchers, and identify new directions for future research in the context of the adoption of digital marketing among TSMEs. The paper presents a theoretical critique of the technology adoption theories and builds on diffusion of innovation theory, technology–organization–environment (TOE), and institutional theory to propose an expanded model to study digital marketing adoption among TSMEs.

The article presents a significant advancement in the theoretical understanding of the adoption of digital marketing by offering the application of the TOE framework with moderating role of mimetic and normative pressures. Thus, the study contributes to the scarce research on institutional theory in the context of services (tourism) and offers an alternative and holistic perception to study digital marketing. The research model serves as an organizing tool for future researchers and practitioners to probe and further augment knowledge development in tourism and TSMEs.

Negligible published work on TSMEs makes this study valuable and the proposed model gives strategic information in the given context.

There is a growing awareness in today's organizations of the gap between existing digital technologies and those arising from digital innovation that contribute to reducing work exhaustion. However, no comprehensive framework has been proposed for the importance of adopting digital innovation in reducing work exhaustion. The purpose of this paper is to provide a holistic view by proposing a model for the importance of adopting digital innovation technologies and their role in reducing work exhaustion in Iraq as a developing country, and the model was proposed based on the theory of technology-organization-environment and diffusion of innovation.

To collect data, an electronic questionnaire was designed for a survey conducted on 183 Iraqi firms in the industrial sector. For data analysis, the structured equation model was used through the (AMOS. 26) program.

The results revealed the importance and significance of the study model in adopting the cloud of things (CoT) as one of the techniques of digital innovation in reducing work exhaustion.

The authors can conclude that the adoption of the CoT in small and medium enterprises (SMEs) can have a positive impact on the performance of the employees. The adoption of the CoT may provide SME managers with an opportunity to effectively manage various roles and responsibilities. While there were many limitations that this study faced, the authors focused on one type of digital innovation dynamics, which is the CoT, as they must focus on other technologies.

To the best of the authors’ knowledge, this study is one of the first studies in Iraq as a developing country that explains how emerging digital innovation can be leveraged to create innovative digital products and services as a CoT technology and subsequently lead to the reduction of work exhaustion. It also fills the literature gaps related to adoption factors of digital innovation and their role in reducing work exhaustion.

This paper aims to identify key theoretical cornerstones and research trends in the apparel industry. It also compares theoretical bases with those of the general research domain in technology adoption literature and, thus, provides future policy guidelines for practitioners and research gaps for further studies.

Documents were collected from the Web of Science (core collection) database using systematic methods. The bibliometric coupling and co-citation analyses were conducted using VOSviewer software to construct theoretical cornerstones and research trends in the apparel industry.

Literature in the apparel industry focuses mainly on the diffusion of innovation and the theory of reasoned action. Hence, the literature lacks investigations of technology–organization–environment and institutional theories for technology adoption in the apparel industry. This study also traces six clusters of prevalent research trends: radiofrequency identification, virtual-try on technology for e-commerce, computer-aided design, Industry 4.0 technologies, virtual-try on technology in design and information technology.

Little research is done on theoretical cornerstones on technology adoption in the apparel industry. This study looks into the theoretical bases for technology adoption, research trends in the apparel supply chain and calls for future research necessities.

This study aims to investigate the factors affecting artificial intelligence (AI) implementation in the accounting industry and compares it among the private and public accounting sectors.

This study uses a theoretical framework that combines the technology–organization–environment model, the innovation diffusion theory model and the technology acceptance model. A convenience sampling method was used to obtain 561 surveys from accounting, finance management, auditing and bookkeeping professionals in public and private organizations in Kuwait. The data were analyzed using the partial least squares structural equation modeling.

This study demonstrates that all individual and organizational variables significantly affect AI implementation in the accounting industry, as supported by adequate values of path coefficient and a p-value of <0.05, except competitive pressure, which did not reach statistical significance. Multi-group analysis indicates statistical differences between the private and public sectors regarding organizational culture, regulatory support and perceived ease of use in AI implementation.

To the best of the authors’ knowledge, this study is the first to compare AI implementation in the private and public accounting sectors. Its findings could redesign the authors’ understanding of AI implementation in the accounting industry.

This study aims to evaluate the knowledge structure of knowledge management (KM) applications within small and medium enterprises (SMEs). In pursuit of excellence, SMEs must adopt KM like large corporations, even with limited resources.

Through a bibliometric approach, this study evaluates current themes based on bibliographic coupling analysis and predicts future trends based on coword analysis. A total of 726 documents and 2,658 keywords were derived from the Web of Science database.

Findings show four clusters in bibliographic coupling and three in coword analysis. A common theme discovered converged on digital technology to ensure SMEs follow current market trends.

Advanced application of Industry 4.0 requires digital transformation for SMEs’ pursuit of excellence. Implications include sustaining SMEs through a considerable KM system integrated with digital technology for sustainable business activities.

To the best of the authors’ knowledge, this study is among the first to provide a science mapping analysis on KM in SMEs by applying a bibliometric analysis.

Introduction: Traditional recruitment system relied heavily on the applicants’ curriculum vitae (CV). This system, besides becoming redundant, has proved to be a futile exercise leading to the hiring of candidates that eventually turn out to be ‘misfits’. CVs were the only source of candidates’ data available for the recruiters a few years back. Face-to-face interviews was considered to be the ultimate solution for hiring suitable candidates. However, evidence suggests that interview scores and job performances do not complement each other. Advancement in artificial intelligence (AI) has introduced several techniques in the recruitment process.

Purpose: This chapter underscores the drawbacks of the traditional recruitment process. Evidence suggests that the traditional recruitment process is prone to subjectivity and is time-consuming. Surprisingly, despite the disadvantages, the integration of AI into the recruitment process is still slow. This chapter highlights the need to harness AI and the advantage technology could bring to the recruitment process. Some of the techniques that are garnering attention and widely used by organisations, such as chatbots, gamification, virtual employment interviews, and resume screening are described to enable the readers to understand with less effort. Chatbots and gamification techniques are described through process flow charts. We also describe the various types of interviews that could be conducted through virtual platforms and the modality by which the resume screening technique operates. Today, we are at a juncture wherein it is pertinent to acknowledge the superiority of technology-driven processes over traditional ones. This chapter will help the readers to understand the modus operandi to implement chatbots, gamification, virtual interviews and online resume screening techniques besides their advantages.

Scope: Although chatbots, resume screening, virtual interviews, and gamification are used in other areas, too, such as training and development, marketing, etc., in this chapter, we restrict solely to employee recruitment processes.

Methodology: Scoping review is used to examine the existing literature from various databases such as Google Scholar, IEEE, Proquest, Emerald, Elsevier, and JSTOR databases are used for extracting relevant articles.

Findings: Automation and analytics in recruitment and selection remove bias which is otherwise increasingly found in manual hiring processes. Also, previous studies have observed that candidates engage in impression management tactics in traditional face-to-face interviews. However, through automated recruitment processes, the influence of these tactics can be eliminated. AI-based virtual interviews reduce human bias. It also helps recruiters to hire talents across the globe. Gamification improves the candidate’s perception of the work and work environments. Through gamified techniques, the recruiters can understand whether a candidate possesses the required job skills. Chatbots are an interactive technique that can respond to interviewees’ queries. Resume screening techniques can save the recruiter’s time by screening and selecting the most appropriate candidates from a large pool. Hence, the chosen candidates alone can be referred to the next stage of the recruitment cycle. AI improves the efficiency of the recruitment process. It reduces mundane tasks. It saves time for the human resources (HR) team.

This paper aims to conduct a systematic review of the literature on supply chain collaboration published over a 10-year period from 2005 to 2014. It explores the nature and extent of research undertaken to identify key themes emerging in the field and gaps that need to be addressed.

The authors review a sample of 207 articles from 69 journals, after using an iterative cycle of defining appropriate search keywords, searching the literature and conducting the analysis.

Key themes include the meaning of collaboration; considerations for supply chain collaboration theory; emerging areas in collaboration for sustainability, technology-enabled supply chains and humanitarian supply chains; and the need for a more holistic approach, multi-tier perspectives and research into B2C collaborations.

The paper provides discussion and scope for future research into the area which would contribute to the field tremendously.

There have been very few reviews in the past on supply chain collaboration, and this is one of the first extensive reviews conducted to address how well the body of knowledge on supply chain collaboration corresponds with our contemporary society.

Thus the purpose of this study is to prioritize the factors affecting the blockchain technology in accounting and auditing practices. Industry 4.0 technology has revolutionized how businesses and professionals perform tasks. Blockchain technology is one such Industry 4.0 technology and has the potential to change the processes used to measure and communicate financial information. More research, particularly in India, is required to better comprehend the use of blockchain in accounting and auditing.

This research used multi-criteria decision-making (MCDM)-based qualitative research approach (“interpretive structural modeling [ISM]” and “cross-impact matrix multiplication [MICMAC]”) to rank and classify the factors affecting blockchain adoption in accounting and auditing.

This study classified environmental, technological and management factors according to driving and dependent powers that enable blockchain adoption in accounting and auditing. The findings of this study showed that top management and government support were the most critical determinants of blockchain adoption in Indian accounting and auditing firms.

This research is one of the few qualitative studies examining the factors affecting blockchain adoption in accounting and auditing processes. After the Indian Government’s 2021 blockchain policy, this study is among the first to assess blockchain adoption factors using multi-criteria decision-making techniques in India to the best of the authors’ knowledge. The findings will assist stakeholders (government, technocrats, service providers, etc.) in increasing blockchain penetration in India’s accounting and auditing sectors.

The purpose of this paper is to identify and analyse collaborative risk management (CRM) literature to establish its current position in supply chain risk management (SCRM) and propose an agenda for future research.

A systematic literature review of 101 peer-reviewed articles over a 21-year period was employed to analyse literature and synthesise findings to clarify terminology, definitions, CRM capabilities, and underlying theory.

CRM as a field of research is in its infancy and suffers from imprecise definitions, fragmented application of capabilities, and diverse theoretical foundations. The term CRM is identified as a more representative description of relational risk management arrangements. Six capabilities relevant to CRM are identified: risk information sharing, standardisation of procedures, joint decision making, risk and benefit sharing, process integration, and collaborative performance systems.

The paper provides a new definition for CRM; proposes a holistic approach in extending collaboration to SCRM; identifies a new capability; and provides a range of theories to broaden the theoretical scope for future research on CRM.