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This study aims to examine the key antecedents influencing the private firm’s intention to adopt big data analytics (BDA) in developing economies. To do so, the study follows the sequential explanatory approach.

To test the hypothesized model that draws on the technology–organization–environment (TOE) framework paired with the diffusion of innovation (DOI) theory, a purposive sampling technique was applied to gather data from 156 IT and management domain experts from the private firms that intend to adopt BDA and operate in Pakistan’s service industry, including telecommunication, information technology, agriculture, and e-commerce. The data were analysed using the partial least squares structural equations modelling (PLS-SEM) technique and complemented with qualitative analysis of 10 semi-structured interviews in NVIVO 12 based on grounded theory.

The empirical findings revealed that the two constructs – perceived benefits and top management support – are the powerful drivers of a firm’s intention to adopt BDA in the private sector, whereas IT infrastructure, data quality, technological complexity and financial readiness, along with the moderators, BDA adoption of competitors and government policy and regulation, do not significantly influence the intention. In addition, the qualitative analysis validates and further complements the SEM findings.

Unlike the previous studies on technology adoption, this study proposed a unique research model with contextualized indicators to measure the constructs relevant to private firms, based on the TOE framework and DOI theory, to investigate the causal relationship between drivers and intention. Furthermore, the findings of PLS-SEM were complemented by qualitative analysis to validate the causation. The findings of this study have both theoretical and practical implications.

Little is known about the extent to which management and engineering publications dedicated to the study of quality management topics make use of mixed methods, what types of studies have been conducted and how effective mixed methods have been. The aim of the current paper is to analyse how mixed methods have been used in quality management research.

To address this purpose, a bibliometric analysis was conducted of papers using mixed methods designs to investigate quality management issues and published in the SCOPUS database. CiteSpace software was used to assist in the categorisation and mapping process.

Ninety articles were identified and analysed. The results show that mixed methods are mainly used either to compare different perspectives drawn from quantitative and qualitative data or to develop better measurement instruments. Sequential mixes occur more often than concurrent approaches. Moreover, there is a link between the purpose of the study and the approaches followed to combine qualitative and quantitative methods. Yet, the contribution of the use of mixed methods to achieving the aims of the study is not easy to assess as the purposes of using mixed methods are often not clearly stated.

As one of the first papers to examine how qualitative and quantitative methods are being combined in quality management research, this study is expected to contribute to the literature by providing some insights into how mixed methods can be more effectively used in this field.

This study aims to investigate how to identify and address production levelling problems in assembly lines utilising an intensive manual workforce when higher productivity levels are urgently requested to meet market demands.

A mixed-methods approach was used in the research design, integrating case study analysis, interviews and qualitative/quantitative data collection and analysis. The methodology implemented also introduces to the literature on operational performance a novel combination of data analysis methods by introducing the use of the Natural Language Understanding (NLU) methods.

First, the findings unveil the impacts on operational performance that transportation, limited documentation and waiting times play in assembly lines composed of an intensive workforce. Second, the paper unveils the understanding of the role that a limited understanding of how the assembly line functions play in productivity. Finally, the authors provide actionable insights into the levelling problems in manual assembly lines.

This research supports industries operating assembly lines with intensive utilisation of manual workforce to improve operational performance. The paper also proposed a novel conceptual model prescriptively guiding quick and long-term improvements in intensive manual workforce assembly lines. The article assists industrial decision-makers with subsequent turnaround strategies to ensure higher efficiency levels requested by the market.

The paper offers actionable findings relevant to other manual assembly lines utilising an intensive workforce looking to improve operational performance. Some of the methods and strategies examined in this study to improve productivity require minimal capital investments. Lastly, the study contributes to the empirical literature by identifying production levelling problems in a real context.

World Health Organizations (WHO) (2023) states that governments and employers have a responsibility to uphold that right by providing work that simultaneously prevents workers from experiencing excessive stress and mental health risks. The business environment continues to produce a lot of stress on workers, which includes internal pressures to achieve results and employees suffer the consequences. Some companies have turned to mindfulness as a technique that helps mitigate these consequences and have joined Kaizen as a process improvement technique in the work environment. Therefore, this study has a research purpose: “to comprehend the possible linkage between Kaizen philosophy from an individual perspective, with Mindfulness ZEN Buddhism technique to understand the individual benefit (well-being) of each employee in organizations.” The answer to this represents the research gap in this article. The research questions governing this study are as follows: RQ1: Does Mindfulness is used as Kaizen technique of personal-individual improvement in 21st-century organizations? RQ2: What elements and characteristics of Kaizen and mindfulness can be found working together? And RQ3: Which qualitative impact of mindfulness and Kaizen in the workplace outcome (well-being, performance of the job (process)) and relationships with other employees)?

This research used a qualitative approach due to the recent phenomenon studied. In a certain way, it was used a mixed-method (combination of qualitative data – web search secondary data analysis and qualitative research-Convergence Model). First, it was done an intensive web search with the aim to identify companies' corporate mindfulness programs, along with companies which have applied mindfulness and Kaizen programs. It was identified a group of big companies with global and international presence (“famous” for their products and services) in diverse industrial and service sectors, country of origin and business locations; with the purpose of getting a holistic vision of all organizations which have practice Kaizen and mindfulness. Therefore, this study explored secondary data related to both practices, analyzing reports or briefings published in management magazines and official WEB pages and/or business magazines.

As a result of the triangulation of the data with its secondary data convergence model and qualitative research, a theoretical framework was reached that shows the benefits of the two combined twin techniques of Kaizen and mindfulness. The worker experiences a path that goes from concentrating on the execution of their processes, following their operating standards (Standardize, Do, Check, Act [SDCA] cycle), going through the evolution to continuous improvement or Plan-Do-Check-Act (PDCA) cycle, experiencing work with concentration-awareness and reducing your daily stress, maintaining high sensitivity to the work process and your environment and finally, discovering an essential life purpose. Finally, worker experiences benefit when there is wide application of both with the SDCA and PDCA cycles such as high motivation, constant learning from your mistakes, day-to-day learning and the Munen Musso (not using the mind).

The main limitation is the qualitative methodological bias and secondary data research. In addition, to have a theoretical sample. However, the richness of the data helps to overcome this limitation. On the other hand, the qualitative research interviews are for a certain geographical area, therefore, the results cannot be generalized.

The results of this research can shed light on operations managers in the use of techniques for continuous improvement and improvement of people's quality of life, such as mindfulness. In Mexico, they are beginning to be used jointly (twin techniques) to comply with Regulation 035 of psychosocial risk, the researchers are sure that in other countries it will be used in the same way to comply with regulations. However, the research findings show the benefits that can be provided to workers in organizations by applying Kaizen and Mindfulness together.

To the best of the authors’ knowledge, according to the literature review, this is the first article that explores the relationship between Kaizen and Mindfulness as twin techniques that help improve the individual quality of life of employees in organizations.

This study aims to test the complaints of tourists who visit five-star hotels in Antalya, Turkey, on those same hotels’ websites.

In the study, the data were collected with qualitative methods but analyzed with the mixed analysis method. In this context, the authors collected 1,012 comments on the website between 2016 and 2019.

According to the results of the study, the most intense complaints were found to be concentrated in categories such as ambience, food and staff.

First of all, it is thought that it will make an important contribution to the literature, since different methodologies are adopted in the study. In addition, online shares, evaluations and comments produce positive or negative results for the destination or business in question. It is necessary to closely monitor such activities in electronic environments, as they may have negative consequences, thus revealing the need to take corrective or preventive measures. For this reason, the research is important in terms of not having such a large-scale study in the literature and contributing to the hospitality industry.

The lack of a definite standard for determining the sample size in qualitative research leaves the research process to the initiative of the researcher, and this situation overshadows the scientificity of the research. The primary purpose of this research is to propose a model by questioning the problem of determining the sample size, which is one of the essential issues in qualitative research. The fuzzy logic model is proposed to determine the sample size in qualitative research.

Considering the structure of the problem in the present study, the proposed fuzzy logic model will benefit and contribute to the literature and practical applications. In this context, ten variables, namely scope of research, data quality, participant genuineness, duration of the interview, number of interviews, homogeneity, information strength, drilling ability, triangulation and research design, are used as inputs. A total of 20 different scenarios were created to demonstrate the applicability of the model proposed in the research and how the model works.

The authors reflected the results of each scenario in the table and showed the values for the sample size in qualitative studies in Table 4. The research results show that the proposed model's results are of a quality that will support the literature. The research findings show that it is possible to develop a model using the laws of fuzzy logic to determine the sample size in qualitative research.

The model developed in this research can contribute to the literature, and in any case, it can be argued that determining the sample volume is a much more effective and functional model than leaving it to the initiative of the researcher.

Positive experiences with working from home (WFH) during the Corona pandemic (COVID-19) have motivated many employees to continue WFH after the pandemic. However, factors influencing employees' WFH intentions against the backdrop of experiences during pandemic-induced enforced working from home (EWFH) are heterogeneous. This study investigates factors linked to information technology (IT) professionals' WFH intentions.

This mixed-methods study with 92 IT professionals examines the effects of seven predictors for IT professionals' WFH intentions. The predictors are categorized according to the trichotomy of (1) characteristics of the worker, (2) characteristics of the workspace and (3) the work context. Structural equation modeling is used to analyze the quantitative survey data. In addition, IT professionals' responses to six open questions in which they reflect on past experiences and envision future work are examined.

Quantitative results suggest that characteristics of the worker, such as segmentation preference, are influencing WFH intentions stronger than characteristics of the workspace or the work context. Furthermore, perceived productivity during EWFH and gender significantly predict WFH intentions. Contextualizing these quantitative insights, the qualitative data provides a rich yet heterogeneous list of factors why IT professionals prefer (not) to work from home.

Reasons influencing WFH intentions vary due to individual preferences and constraints. Therefore, a differentiated organizational approach is recommended for designing future work arrangements. In addition, the findings suggest that team contracts to formalize working patterns, e.g. to agree on the needed number of physical meetings, can be helpful levers to reduce the complexity of future work that is most likely a mix of WFH and office arrangements.

This study extends literature reflecting on COVID-19-induced changes, specifically the emerging debate about why employees want to continue WFH. It is crucial for researchers and practitioners to understand which factors influence IT professionals' WFH intentions and how they impact the design and implementation of future hybrid work arrangements.

There is a growing need for methodological plurality in advancing operations management (OM), especially with the emergence of machine learning (ML) techniques for analysing extensive textual data. To bridge this knowledge gap, this paper introduces a new methodology that combines ML techniques with traditional qualitative approaches, aiming to reconstruct knowledge from existing publications.

In this pragmatist-rooted abductive method where human-machine interactions analyse big data, the authors employ topic modelling (TM), an ML technique, to enable constructivist grounded theory (CGT). A four-step coding process (Raw coding, expert coding, focused coding and theory building) is deployed to strive for procedural and interpretive rigour. To demonstrate the approach, the authors collected data from an open-source professional project management (PM) website and illustrated their research design and data analysis leading to theory development.

The results show that TM significantly improves the ability of researchers to systematically investigate and interpret codes generated from large textual data, thus contributing to theory building.

This paper presents a novel approach that integrates an ML-based technique with human hermeneutic methods for empirical studies in OM. Using grounded theory, this method reconstructs latent knowledge from massive textual data and uncovers management phenomena hidden from published data, offering a new way for academics to develop potential theories for business and management studies.

The purpose of this study is to identify the impact of online learning on university librarians’ professional development and library services.

A mixed-methods study through an explanatory research design was applied to address the study’s objectives. Quantitative data were gathered from 341 librarians working in 221 universities, while qualitative data were gathered from 27 experts working in 21 different universities of Pakistan.

The findings of the study revealed that online learning has a significant positive impact on the professional development of university librarians. Results revealed that online learning assists in the provision of sustainable, innovative library services in university libraries.

The study has offered a model in light of the study's quantitative and qualitative findings. It contributes to theoretical understanding by expanding the existing knowledge base. It offers managerial insights, enabling the development of policies that foster the professional development of library personnel and the implementation of smart library services.

The main purpose of the study is to reveal the hotel managers' perspectives strategies, and predictions on smart technologies, and their expectations for current staff and potential staff to be employed in the future.

A qualitative research approach was used to reveal the internal perspectives of managers to determine their Smart Tourism (ST) perspectives. With the snowball sampling method, face-to-face interviews were conducted with 16 senior hotel managers working in a 5-star hotel in Antalya. The data obtained were carried out with inductive content analysis and descriptive analysis from qualitative research analysis methods.

In this study, hotel managers' broad perspectives on ST were discussed in depth and presented comprehensively. Managers' perceptions of smart technologies are classified in terms of aggregate dimensions and themes. Among the most important findings, rapidity/quickness, managing/holistic assessment, standardization, harmony/integration-coordination and experience-memory, defined as the crossroads of total dimensions or the heart of smart technologies, were identified as the most important themes. In addition, Stylos et al. (2021), another important finding is the classification of technologies used in top-quality hotels, based on the conceptual framework for smart technologies presented in the literature.

The effective and efficient use of technology, its internalization and openness to technology provides important advantages in hotels such as increasing revisits and satisfaction, providing loyalty and reducing costs. Thus, the perceptions, practices, strategies and prediction of senior managers working in high-level hotels about ST provide valuable data to other hotels that want to survive in the competition.

From a theoretical point of view, this study is valuable in that it deals with the ST perceptions of senior managers with an exploratory research approach. Managerially, the research findings offer valuable contribution about the attitudes, trends, forecasts and expectations of senior managers working in high-level hotels towards ST.