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Sentiment analysis is a text analysis method that is developed for systematically detecting, identifying, or extracting the emotional intent of words to infer if the text expresses a positive or negative tone. Although this novel method has opened an exciting new avenue for organizational research – mainly due to the abundantly available text data in organizations and the well-developed sentiment analysis techniques, it has also posed a serious challenge to many organizational researchers. This chapter aims to introduce the sentiment analysis method in the text mining area to the organizational research community. In this chapter, the authors first briefly discuss the central role of sentiment in organizational research and then introduce the traditional and modern approaches to sentiment analysis. The authors further delineate research paradigms for text analysis research, advocating the iterative research paradigm (cf., inductive and deductive research paradigms) that is more suitable for text mining research, and also introduce the analytical procedures for sentiment analysis with three stages – discovery, measurement, and inference. More importantly, the authors highlight both the dictionary-based and machine learning (ML) approaches in the measurement stage, with special coverage on deep learning and word embedding techniques as the latest breakthroughs in sentiment and text analyses. Lastly, the authors provide two illustrative examples to demonstrate the applications of sentiment analysis in organizational research. It is the authors’ hope that this chapter – by providing these practical guidelines – will help facilitate more applications of this novel method in organizational research in the future.

This research aims to investigate the process of value creation, value delivery, and value capture in project-based companies. Most previous research focused on companies that operate regularly and offer manufactured products or services. This research used companies in the field of information technology that developed software to explain how value creation, value delivery, and value capture occurred. A case study with qualitative research was applied to analyze between cases. Empirical findings showed that companies carry out six activities to ensure that value creation, value delivery, and value capture can be realized in the software development process. The six activities were iterative and not a rigid sequence. This research was limited to the software industry, and further research can test the results of this study by using a survey to increase the generalizability theory developed in this study.

This chapter of the book aims to introduce multiobjective linear programming (MLP) as an optimum tool to find the best quality engineering techniques (QET) in the main domains of supply chain management (SCM). The importance of finding the best quality techniques in SCM elements in the shortest possible time and at the least cost allows all organizations to increase the power of experts’ analysis in supply chain network (SCN) data under cost-effective conditions. In other words, this chapter aims to introduce an operations research model by presenting MLP for obtaining the best QET in the main domains of SCM. MLP is one of the most determinative tools in this chapter that can provide a competitive advantage. Under goal and system constraints, the most challenging task for decision-makers (DMs) is to decide which components to fund and at what levels. The definition of a comprehensive target value among the required goals and determining system constraints is the strength of this chapter. Therefore, this chapter can guide the readers to extract the best statistical and non-statistical techniques with the application of an operations research model through MLP in supply chain elements and shows a new innovation of the effective application of operations research approach in this field. The analytic hierarchy process (AHP) is a supplemental tool in this chapter to facilitate the relevant decision-making process.

Common literature review methods such as systematic review and narrative review are poorly suited to the investigation of complex management phenomena. Systematic reviews are highly driven by protocol and procedure, and are oft-criticized as reductive and poorly equipped to examine the interaction between phenomena and context, nonlinear processes, and empirical outcomes that are less predictable. Narrative reviews, on the other hand, are pluralistic and iterative and thus better suited to descriptions of the complex and unpredictable; however, they tend to lack methodological transparency, trustworthiness, and pragmatism in application. The “realist synthesis” approach to literature review can be seen as the middle-ground between these two common methods, offering both methodological rigor alongside flexibility and nuance. Realist synthesis takes an explanatory frame, with a focus on unearthing the theorized causal mechanisms at play beneath a phenomenon of interest.

Entrepreneurial identity is a complex concept. It has been recognised as a subjective and dynamic socio-cognitive factor which is not stable over time and is part of an iterative formation process. This chapter explores the journey of adopting, implementing and reviewing visual methods, in order to examine entrepreneurial identity, from the researchers’ perspectives. A critical standpoint is offered which explores both the benefits and challenges that presented themselves in the search for rich data.

Entrepreneurship education is being taught to undergraduates in tertiary institutions and fresh graduates in youth programmes to encourage start-ups and create employment as a strategy to stem youth unemployment. As such, entrepreneurship education programmes are expected to include rigorous processes of programme design, implementation and evaluation so as to achieve changes in behaviour, attitude and action of participants measureable in terms of start-up and jobs created. Two entrepreneurship education programmes implemented in Nigeria are evaluated to ascertain the level of effectiveness in design, implementation and evaluation and the outcomes in terms of start-ups and employment created. Research methods adopted in the two programmes combine observation techniques with content analyses, action research in case study and focus group interviews. In addition, test-retest techniques in a quasi-experimental design, with a structured questionnaire is adopted in programme number two only. The findings are that while it is suspected that the design stage is jumped in programme number one, in programme two, the design is poorly done. Implementation is ineffective in the two programmes because objectives did not arise from programme design as they ought to and evaluation methods are inappropriate and so ineffective. The recommendations include review of the design of the two programmes to generate appropriate and measurable objectives; adopting implementation strategies that will achieve the measurable objectives generated from revised programme designs and adopting appropriate evaluation techniques that has capacity to measure outcomes and impact in addition to outputs.

The development of qualitative research methods addresses the need to explore, understand and interpret complex and subjective phenomena across various fields of study. These methods are guided by methodological frameworks, and data collection involves taking several precautions for observation or interviews. While these guidelines facilitate an emphasis on the objective aspects of discourse, accounting for subjectivity and emotions proves more challenging. However, these subjectivity and emotions are deemed as significant sources of information. In this chapter, we propose an innovative data collection method centred around creating collages and engaging in group discussions to decipher their meaning. Collage serves as a visual medium, and we recommend utilising semiotic analysis tools to comprehend its significance. To gain a more precise understanding of the value of collage as a data collection method, we studied a collage workshop organised by CREE. Through image analysis and exchanges, our findings reveal that collage acts as a physical medium that fosters exchanges, deepens ideas and restricts digressions. Additionally, collage allows for the expression and discussion of emotions linked to the image rather than the individual. The space of intersubjective reflexivity facilitated by collage enables a profound comprehension, critical assessment and augmentation of ideas and the interpretation of emotions without compromising the sensitivity of the author. This chapter’s main contribution is evidently manifested here.

Processual approaches to entrepreneurship have increasingly captured researchers’ interest. One such approach that tries to understand entrepreneurs in real time by looking with them, not at them, has been termed withness (Shotter, 2006). But how does one design a study that captures this experience of living in the flow? In this methodological reflection, we propose using the metaphor of warp and weft to think of grounded theory research designs that seek to approximate withness. To this end, we also reflect on our experience studying the unfolding processes in international new ventures and highlight the usefulness of multiple data collection instruments, notably diaries and interviews.