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This chapter examines the application of exploratory sequential mixed methods design in the context of small accommodation enterprises (i.e., home-stay). This study, therefore, discusses the exploratory sequential mixed methods of data collection and analysis and provides practical illustrations based on a study of small tourism enterprise sustainability practices in Ghana. The findings demonstrate that mixed methods overcome the weaknesses of a mono-method and offer an in-depth understanding of tourism and hospitality phenomena. In addition to providing a practical guide to emerging tourism scholars, the current study highlights the ability of mixed methods to develop emerging practitioners' skills in both qualitative and quantitative data. In conclusion, the exploratory sequential mixed methods design offers pragmatic data collection techniques that are non-existent in mono-methods. Accordingly, it is recommended for exploring research questions when there is limited information and high flexibility is needed.

Citizens are substantial stakeholders in every e-government system, thus their willingness to use and ability to access the system are critical. Unequal access and information and communication technology usage, which is known as digital divide, however has been identified as one of the major obstacles to the implementation of e-government system. As digital divide inhibits citizen’s acceptance to e-government, it should be overcome despite the lack of deep theoretical understanding on this issue. This research aimed to investigate the digital divide and its direct impact on e-government system success of local governments in Indonesia as well as indirect impact through the mediation role of trust. In order to get a comprehensive understanding of digital divide, this study introduced a new type of digital divide, the innovativeness divide.

The research problems were approached by applying two-stage sequential mixed method research approach comprising of both qualitative and quantitative studies. In the first phase, an initial research model was proposed based on a literature review. Semi-structured interview with 12 users of e-government systems was then conducted to explore and enhance this initial research model. Data collected in this phase were analyzed with a two-stage content analysis approach and the initial model was then amended based on the findings. As a result, a comprehensive research model with 16 hypotheses was proposed for examination in the second phase.

In the second phase, quantitative method was applied. A questionnaire was developed based on findings in the first phase. A pilot study was conducted to refine the questionnaire, which was then distributed in a national survey resulting in 237 useable responses. Data collected in this phase were analyzed using Partial Least Square based Structural Equation Modeling.

The results of quantitative analysis confirmed 13 hypotheses. All direct influences of the variables of digital divide on e-government system success were supported. The mediating effects of trust in e-government in the relationship between capability divide and e-government system success as well as in the relationship between innovativeness divide and e-government system success were supported, but was rejected in the relationship between access divide and e-government system success. Furthermore, the results supported the moderating effects of demographic variables of age, residential place, and education.

This research has both theoretical and practical contributions. The study contributes to the developments of literature on digital divide and e-government by providing a more comprehensive framework, and also to the implementation of e-government by local governments and the improvement of e-government Readiness Index of Indonesia.

In this chapter, the authors discuss challenges and decision-making in the process of conducting quality mixed methods research in higher education, and offer the lessons learned from their experiences. The chapter begins with a discussion of quality and the ways of establishing quality in mixed methods studies. Two examples of studies are used to illustrate the issues involved in addressing quality in conducting mixed methods studies in different higher education settings. The first example discusses the challenges associated with establishing the quality of meta-inferences in a mixed methods (quantitative to qualitative) design that was used in two studies of students’ engagement and persistence in pursuing graduate degrees online in the United States. The second example presents the methodological steps and criteria for evaluating the quality of a multilevel mixed design study to explain quality management in Greek higher education. The authors also reflect on how researchers can become active participants in the co-construction of quality in mixed methods research.

Discrete event simulation (DES) is widely known to be a quantitative research tool. A simulation modelling process is mainly based on feeding quantitative data into a model to produce quantitative results in a structured sequential process. Qualitative approaches to research take a less structured approach with more of an inclination towards judgmental and expert knowledge rather than hard data. In this paper the authors suggest that DES can be employed as both a qualitative and quantitative research tool. The paper demonstrates how simulation may represent both stances either separately or combined. This is based on the fact that the basic objectives of simulation are either for understanding – which needs a qualitative perspective – or performance measurement – which a needs quantitative perspective. Traditional quantitative and qualitative methods are discussed showing how DES might cope with the weaknesses of both stances. A structure for using DES as a combined research methodology is proposed.

This paper aims to represent a response to issues raised in the continuing quantitative-qualitative debate by Valtakoski (2020). Which appeared in a Journal of Services Marketing (JSM) special issue on qualitative research in service-oriented research.

The authors performed a content analysis of 1,268 papers that were published in JSM (1987-2019). In addition, the authors had data that is held in JSM’s manuscript central submission portal.

The analysis shows that while there is a dominance of quantitative methods in the journal, the proportion of qualitative papers is growing. During 2014-2019, 83.4 per cent of submitted papers to JSM represented quantitative research and 14 per cent represented qualitative research; however, 75 per cent of accepted papers were quantitative and 25 per cent were qualitative/mixed methods. Thus, the proportion of published qualitative studies are increasing and have a higher chance of receiving an acceptance decision compared to quantitative studies. Additionally, the largest percentage of qualitative papers published in JSM derive from corresponding authors outside of North America.

Service researchers who opt to use inductive research methods, which tend to use qualitative research, will not confront discrimination based solely upon the use of a research methodology among editors or reviewers at JSM.

JSM welcomes qualitative research that has rich practical implications.

This study is one of the first to provide authors with a detailed analysis and responses to the qualitative-quantitative debate in marketing.

The purpose of this paper is to set the scene for this special issue by synthesising the vast array of literature to examine what constitutes mixed methods research, and the associated strengths and risks attributed to this approach.

This paper takes the form of a literature review. The authors draw on extensive methods research from a diverse range of social science disciplines to identify and explore key definitions, opportunities and risks in mixed methods studies. They review a number of accounting studies that adopt mixed methods research approaches. This allows the authors to analyse variance in how mixed methods research is conceptualised across these studies and evaluate the perceived strengths and limitations of specific mixed methods design choices.

The authors identify a range of opportunities and challenges in the conduct of mixed methods research and illustrate these by reference to both published studies and the other contributions to this special issue.

With the exception of Modell's work, there is sparse discussion of the application and potential of mixed methods research in the extant accounting literature.

While investor relations have become an established corporate function, research into how investor relations officers (IROs) practice measurement and evaluation is limited. The purpose of this paper is to examine which approaches and metrics IROs use to gauge their success.

To address this gap in the literature, this study surveyed (n=384) the corporate membership of the National Investor Relations Institute (NIRI), the world's largest investor relations association, on the topic of measurement and evaluation.

The results indicate that IROs strongly (80 percent) believe that mixed-methods (i.e. both quantitative and qualitative methods) should be used to measure the success of investor relations. Mixed-methods advocates place significantly more importance on measurement than IROs that prefer quantitative- or qualitative-only approaches.

The results of this survey indicate that IROs typically place the most value on metrics that are qualitative, non-financial and relationship-oriented. These findings suggest that IROs believe they should be evaluated in large part on their competency at relationship management.

From a benchmarking perspective, these findings suggest that IROs looking to align with their peers should use a mix of both quantitative and qualitative evaluation measures that are non-financial and relationship management-focused.

These findings contribute to recent efforts to explicate a general theory of investor relations. While investor relations scholarship has grown in recent years, up until this point, little attention had been paid to measurement and evaluation.

Mixed methods research is an approach for blending quantitative and qualitative data analyses in a single study. It emerged as an alternative to the dichotomy of qualitative and quantitative traditions in the past 20 years. Some strengths of mixed methods research include the ability to generate and test theory, the capability to answer complex research questions, and the possibility of corroborating findings.

We argue the mixed methods approach fits well with comparative education studies because they seek to acquire data to make sound and meaningful comparisons about the experience and performance of education systems in different countries. By nature, comparative education attempts to explain why educational systems vary and to explore how education relates to wider social factors and forces. It consists of both confirmatory and exploratory inquiries that are based on the fundamental belief that education can be improved in all nations. Essentially, the mixed methods approach can adequately support the goals of comparative education studies, with its quantitative components serving the confirmatory objectives and the qualitative components attending to the exploratory end.

In this study, we conducted a survey of articles published between 2000 and 2014 in Comparative Education Review, Comparative Education, and Compare to discern the changes in patterns and preferences of dominant research methods. By surveying the three major journals in the field, we hope to reveal the means by which comparative education is conducted in its constituency. At the very least, we believe our study can provide important reference points for speculation about where comparative education might be headed in terms of methodology and methods.

The purpose of this paper is to describe how to implement mixed methods research in supply chain management.

A review of past journal analyses on research methods used in supply chain management‐related disciplines is conducted to demonstrate the low incidence of mixed methods research in supply chain management. Drawing from literature on multiple and mixed methods research, the paper provides guidelines for designing and reporting such studies.

Knowledge development in logistics and supply chain management relies primarily on single‐method quantitative research designs, while mixed methods approaches are rarely used. Thus, there is a significant opportunity to advance the discipline through the rigorous application of mixed methods research.

Supply chain management phenomena are complex and dynamic. Thus, the application of mixed methods research would serve the advancement of the discipline as these approaches provide richer understanding and more robust explanations of such phenomena.

If supply chain research is to keep up with the dynamic business environment, research methods must be applied with the capability to fully explain supply chain phenomena. The application of a single‐method research approach is not always adequate for this task.

This paper is the first to draw on research from various disciplines to investigate the use of mixed methods in logistics and supply chain management research. It examines its prevalence in the discipline, provides examples of its application from the supply chain management literature, prescribes how to implement mixed methods research, and describes the benefits and limitations of such designs.

Consumers increasingly rely on organisations for online services and data storage while these same institutions seek to digitise the information assets they hold to create economic value. Cybersecurity failures arising from malicious or accidental actions can lead to significant reputational and financial loss which organisations must guard against. Despite having some critical weaknesses, qualitative cybersecurity risk analysis is widely used in developing cybersecurity plans. This research explores these weaknesses, considers how quantitative methods might address the constraints and seeks the insights and recommendations of leading cybersecurity practitioners on the use of qualitative and quantitative cyber risk assessment methods.

The study is based upon a literature review and thematic analysis of in-depth qualitative interviews with 16 senior cybersecurity practitioners representing financial services and advisory companies from across the world.

While most organisations continue to rely on qualitative methods for cybersecurity risk assessment, some are also actively using quantitative approaches to enhance their cybersecurity planning efforts. The primary recommendation of this paper is that organisations should adopt both a qualitative and quantitative cyber risk assessment approach.

This work provides the first insight into how senior practitioners are using and combining qualitative and quantitative cybersecurity risk assessment, and highlights the need for in-depth comparisons of these two different approaches.