Search results

Mixed methods research is useful to enhance theoretical and practical research contributions. However, single methods have predominated much logistics and supply chain management (LSCM) research. This paper presents a review of mixed methods research across ten years in LSCM to determine their usage, identify benefits and inhibitors, and provide suggestions for LSCM researchers to realise the benefits from using mixed methods.

This paper adopts a mixed methods approach through a quantitative analysis of methods used in six leading LSCM journals, an e-mail survey of mixed methods article authors during the review period, and four published case studies that used mixed methods.

Only 144 (ten percent) of all empirical articles were published using mixed methods during the review period. A range of benefits and inhibitors regarding mixed methods adoption were found. Suggestions for LSCM authors include research training in mixed methods use and developing a project-specific research design due to the specificity and complexity associated with mixed methods research.

LSCM is at a critical juncture, shaped by new contexts, themes and challenges, and would benefit from different research approaches and methods. This paper contributes to the LSCM domain through analysing the current state, benefits and inhibitors of mixed methods research in LSCM journals to provide a renewed call to action and guidelines for mixed methods LSCM research, and suggesting research design adaptation to enable agile and resilient research when investigating rapidly changing and complex phenomena.

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 research intends to develop a model for predicting employees at a high-risk attrition and identify the most important factors affecting them.

In this study, using the triangulation technique of a mixed research method, the employee attrition problem is investigated by identifying its affecting factors. For that matter, data related to the human resources department of a pharmaceutical company in Iran are used. And to achieve the intended goal, advanced data mining algorithms and interviews with human resource managers are applied.

A model for predicting employees at a high-risk attrition is presented based on the gradient boosting machine algorithm with 89% accuracy. The use of the mixed research approach shows that qualitative and quantitative methods can be more effective in identifying the factors affecting employee churn or loss of staff. The results also contain a new situation arising out of the COVID-19 pandemic and remote working scenarios having impact on employee attrition. Finally, human resource policies are presented based on variables related to each of the identified factors.

The novel contributions of this study include real data related to a leading pharmaceutical company as well as a combination of two quantitative and qualitative methods. The hybrid approach can identify the reasons for attrition and, consequently, retention policies to benefit from the advantage of both approaches. Data mining can be useful to identify the factors, which are usually not mentioned in termination interviews, such as direct managers. On the other hand, the results obtained from termination interviews can also include features that the authors cannot identify through data mining, which are specifically related to the characteristics of the pharmaceutical industry such as building a more professional career path. From a practical perspective, since this company specializes in pharmaceutical marketing in a new way and is primarily comprised graduates, it is important to note that the churn of specialized people disperses organizational and technological know-how. On the other hand, the pharmacist community in Iran is small, and their attrition might adversely affect not only the reputation of an organization but the employer's brand as well. So, this research would help other similar firms in retaining their valuable human capital.

Sustainability has become a global need for survival in every field since the side effects of financial development have resulted in environmental devastation. Green banking (GB) has been proposed as a way to reduce the carbon footprint caused by banking operations by promoting paperless financial services through the intensive use of technology. However, the adoption level of GB technology remains unsatisfactory among customers in the United Arab Emirates (UAE). Therefore, using the unified theory of acceptance and use of technology (UTAUT), this study aims to comprehensively investigate the challenges affecting the intention of bank consumers in the UAE to adopt GB technology.

This study used exploratory sequential mixed-methods research. Preliminary semi-structured interviews were conducted with ten banking professionals using a purposive sampling technique to explore the challenges affecting consumers’ intention to adopt GB technology. Sequentially, the study tested various factors through a quantitative cross-sectional online survey of a sample of 332 bank customers and used the convenience sampling technique to obtain further empirical support for the research framework. Thematic content analysis using NVivo 11 was used for the qualitative data analysis. Meanwhile, partial least square structural equation modelling in Smart PLS 3.3 was used for the quantitative data analysis.

The qualitative analysis identified six new challenges affecting customers’ intention to adopt GB technology, including customer awareness, personal innovativeness, bank reputation, security and privacy, system quality and government support. The preliminary qualitative findings were confirmed mainly through quantitative data analysis, whereby customer awareness, personal innovativeness, system quality and bank reputation were found to significantly impact customers’ intention to adopt GB technology. However, the effects of security and privacy and government support were insignificant.

To the best of the authors’ knowledge, this study is the first to propose a comprehensive model that considers individual, technological, organisational and environmental factors to address the issue of customers’ low GB technology adoption rates in the UAE. Meanwhile, this study extends the UTAUT by integrating new factors. This paper is also among the first to investigate customers’ GB technology adoption intention using a mixed-methods approach, which combines the strengths of quantitative and qualitative methods within the same study to offer better insights than a single-method approach.

The lockdown of schools to control the spread of Coronavirus Disease 2019 (COVID-19) has adversely affected elementary and secondary school students in China. However, little evidence is available that documents their perceptions toward the use of e-learning under the pandemic context. This study aims to explore (1) the underlying determinants influencing the students' intentions to continue e-learning and (2) the role that the COVID-19 pandemic plays in this decision. This study extends the expectation–confirmation model (ECM) through a mixed-methods study.

This study uses a mixed-methods approach. Phase 1 draws conclusions and extracts significant elements related to e-learning during the pandemic by analyzing students' user reviews from platforms. Based on the findings, the authors identify the relevant variables and develop an extended ECM by integrating attitudes and the perceived threat of COVID-19. In Phase 2, the research model is empirically validated using data collected from 36,920 elementary and secondary school students in China. This study uses a mixed-methods approach. Phase 1 draws conclusions and extracts significant elements related to e-learning during the pandemic by analyzing students' user reviews from platforms. Based on the findings, the authors identify the relevant variables and develop an extended ECM by integrating attitudes and the perceived threat of COVID-19. In Phase 2, the research model is empirically validated using data collected from 36,920 elementary and secondary school students in China.

In Phase 1, the results reveal that students' most concern elements in the COVID-19 pandemic are user perceptions toward e-learning and threat perceptions of COVID-19. In Phase 2, the results reveal that perceived usefulness and attitude are the most significant factors in students' intention to continue. The perceived threat of COVID-19 indirectly influences their intention to continue.

The study extends the ECM with a mixed-methods study to understand students' perceptions toward e-learning during the COVID-19 pandemic. This study can be helpful in related studies in the context of COVID-19-related diseases or other novel scenarios.

This study aims to develop and test a model of the antecedents, mediators and consequences of the glass cliff phenomenon through public sector service organizations in Iran to explore more insights on gender inequality in managerial positions.

The current research was conducted based on a mixed-method approach, using both qualitative and quantitative research designs. First, the qualitative method includes content analysis by conducting semi-structured interviews with 20 university professors and expert managers working in public sector service organizations in Iran. The outcomes of the qualitative phase lead to designing the conceptual framework and research hypothesis. Then, through a quantitative phase, 384 female managers working in public sector service organizations in Iran are selected using stratified random sampling and fill out the research questionnaire. The exploratory factor analysis was used to verify the model. Moreover, structural equation modeling, using AMOS 24, was used to test the research hypothesis.

The findings of the qualitative phase were represented in three categories including antecedents (e.g. the characteristics of women’s leadership, the selection of women based on meritocracy criteria, women’s preferences and organizational factors), mediation effect (e.g. succession planning, personal development planning and support networks) and consequences of the glass cliff phenomenon (e.g. positive and negative consequences). The results of the exploratory factor analysis show there are ten components, explaining 88.5% of variances. Moreover, the test of the structural model supports the direct effect of antecedents on the glass cliff phenomenon. The results also show the effect of the glass cliff phenomenon on consequences through mediation effects.

There are some limitations that can be addressed by other researchers. Accordingly, the limited number of female managers in Iran prevented larger quantitative research. Moreover, the current research only found casual and mediation consequences of the glass cliff phenomenon, and potential moderators were not considered in this study.

The present study’s innovations may include using a mixed-method approach to investigate the antecedents, mediators and consequences of the glass cliff phenomenon in this study and examining the model constructs in some public sector service organizations. This research may provide a deep understanding of the antecedents, mediators and consequences of the glass cliff phenomenon by finding new factors using a mixed-method approach.

Conducting mixed methods (MM) research is one of many ways to study a research topic in the hospitality and tourism domain. This paper aims to offer a synopsis and guidelines on the application of MM research design within hospitality and tourism.

This paper summarizes the pivotal information on how to write high-quality MM research papers. In doing so, the paper draws on common practices and advice from previous books and articles as well as advice from the editor-in-chief and one of the associate editors of the International Journal of Contemporary Hospitality Management.

This study provides explanations, guidelines and examples of MM research design.

It offers specific recommendations and examples of MM research design in the hospitality and tourism field. This study concludes with a discussion of common mistakes, useful tips and a framework for the self-assessment of MM research.

This is one of the few studies providing specific guidance and recommendations on designing MM research papers in hospitality and tourism studies.

This study aims to explore the interaction among individual factors (enjoyment in helping others and knowledge self-efficacy), organizational factors (top management support and organizational rewards) and the use of information and communication technology factors as enablers of knowledge-sharing (KS) processes (knowledge donating and knowledge collecting) and firm innovation capability (IC) in a telecommunications company in an emerging market economy, namely, Bahrain.

The study used a mixed-methods case study approach. It used answers from 77 employees’ questionnaires and applied the partial least squares structural equation modeling method to test the research model. Several in-depth semidirective interviews were conducted with managers from different levels, functions and educational qualifications to address additional social, cultural, structural and strategic issues related to KS and IC.

The results indicated that enjoyment of helping others correlates with knowledge collection. Top management support had a substantial connection with knowledge donation, which had a robust positive relationship with firm IC. The interviews showed that moving toward a customer-centric strategy, policies, procedures and KS culture in a big organization with many business silos required tremendous effort and pain. People’s ability, willingness and readiness to share knowledge heavily depend on the corporate culture. Employee resistance to change posed a significant challenge.

Researchers have rarely used a case study or a mixed-methods case study approach to explore KS and IC. This study aims to fill this gap using a mixed-methods approach to examine KS enablers, processes and IC in a developing country’s social and cultural context, Bahrain. The work brings together new ways of looking at things and figuring out what they mean to understand knowledge transfer and IC in a telecommunications company. The company must incur changes and additions to its KS mechanisms to inspire innovation.

Despite considerable research on the subject, there is still some misunderstanding about what characterizes successful project delivery in construction projects. Evaluating project delivery success is crucial for organizations since it enables them to prepare for future growth through more effective project management mechanisms and rank the organization's projects for continuous improvement. There is considerable disagreement over a set of success criteria that can be applied to all kinds of projects when evaluating project delivery success, making it a complicated procedure for practitioners and scholars. This research seeks to alleviate the problem by validating and testing a systematic project delivery success model (3D integration model) in the Australian construction industry. The aim is to establish a dependable approach built upon prior research and reliable in evaluating delivery success for any project type.

Based on a novel project delivery success model, this research applies a case study methodology to analyse 40 construction projects undertaken by a single Australian project management consultancy. The research utilizes a mixed-method research approach and triangulates three sets of data. First, the project delivery success (PDS) scores of the projects are calculated by the model. Second, a qualitative analysis targeting the performance of the same projects using a different system called the performance assessment review (PAR) scores was obtained. These culminate in two sets of ranking. The third step seeks validation of results from the head of the partnering organization that has undertaken the projects.

The findings of this study indicate that the 3D integration model is accurate and reliable in measuring the success of project delivery in construction projects of various sizes, locations and durations. While the model uses six key performance indicators (KPIs) to measure delivery success, it is evident that three of these may significantly improve the likelihood of PDS: value, speed and impact. Project managers should focus on these priority aspects of performance to generate better results.

Restrictions inherent to the case study approach are identified for this mixed-method multiple-case study research. There is a limitation on the sample size in this study. Despite the researcher's best efforts, no other firm was willing to share such essential data; therefore, only 40 case studies could be analysed. Nonetheless, the number of case studies met the literature's requirements for adequate units for multiple-case research. This research only looked at Australian construction projects. Thus, the conclusions may not seem applicable to other countries or industries. The authors investigated testing the PDS in the construction sector. It can assist in improving efficiency and resource optimization in this area. Nonetheless, the same technique may be used to analyse and rank the success of non-construction projects.

Despite the research conducted previously on the PDS of construction projects, there is still confusion among researchers and practitioners about what constitutes a successful project delivery. Although several studies have attempted to address this confusion, no consensus on consistent performance metrics or a practical project success model has been formed. More importantly, (1) the ability to measure success across multiple project types, (2) the use of triple bottom line (TBL) to incorporate sustainability in evaluating delivery success and (3) the use of a complexity measurement tool to adjust delivery success scores set the 3D integration model apart from others.