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The purpose of this paper is to present a conceptual framework for integrating strategic thinking factors, organisational performance and the decision-making process.

The methodology involves a synthesis of literature and proposes a framework that explores the relationship between strategic thinking enabling factors, organisational performance and the moderating effect of decision-making styles.

The framework includes strategic thinking enabling factors (systems perspective, focused intent, intelligent opportunism, thinking in time and hypothesis-driven analysis), organisational performance and the moderating effect of decision-making styles (intuitive and rational).

This research results in a conceptual model only; it remains to be tested in actual practice. The expanded conceptual framework can serve as a basis for future empirical research and provide insights to practitioners into how to strengthen policy development in a strategic planning process.

A paradigm shift in the literature proves that strategic management and decision-making styles are vital in determining organisational performance. This paper highlights the importance of decision-making styles and develops a framework for strategic management by analysing the existing strategic management literature.

Managers must make numerous strategic decisions in order to initiate and implement a business model innovation (BMI). This paper examines how managers perceive the management team interacts when making BMI decisions. The paper also investigates how group biases and board members’ risk willingness affect this process.

Empirical data were collected through 26 in-depth interviews with German managing directors from 13 companies in four industries (mobility, manufacturing, healthcare and energy) to explore three research questions: (1) What group effects are prevalent in BMI group decision-making? (2) What are the key characteristics of BMI group decisions? And (3) what are the potential relationships between BMI group decision-making and managers' risk willingness? A thematic analysis based on Gioia's guidelines was conducted to identify themes in the comprehensive dataset.

First, the results show four typical group biases in BMI group decisions: Groupthink, social influence, hidden profile and group polarization. Findings show that the hidden profile paradigm and groupthink theory are essential in the context of BMI decisions. Second, we developed a BMI decision matrix, including the following key characteristics of BMI group decision-making managerial cohesion, conflict readiness and information- and emotion-based decision behavior. Third, in contrast to previous literature, we found that individual risk aversion can improve the quality of BMI decisions.

This paper provides managers with an opportunity to become aware of group biases that may impede their strategic BMI decisions. Specifically, it points out that managers should consider the key cognitive constraints due to their interactions when making BMI decisions. This work also highlights the importance of risk-averse decision-makers on boards.

This qualitative study contributes to the literature on decision-making by revealing key cognitive group biases in strategic decision-making. This study also enriches the behavioral science research stream of the BMI literature by attributing a critical influence on the quality of BMI decisions to managers' group interactions. In addition, this article provides new perspectives on managers' risk aversion in strategic decision-making.

The purpose of this paper is to gain insight into the contingent use of rational, intuitive and political decision-making in R&D.

This research is based on a study in an R&D department of a multinational high-tech firm in the Netherlands. The study consists of a case study design, focusing on four embedded cases, longitudinally studying each case.

The literature distinguishes three dimensions of innovation decision-making processes: rational, intuitive and political. By studying these interwoven dimensions over time, this study finds that the dominant use of each of these dimensions differs across the innovation process. There is an emphasis on intuitive decision-making in an early phase, followed by more emphasis on political decision-making, and moving to more emphasis on rational decision-making in a later phase of the R&D process. Furthermore, the predominant choice in a specific innovation phase for one of the three decision-making dimensions is influenced by the decision-making dimension that is dominantly employed in the preceding phase.

This study contributes to the innovation decision-making literature by developing and applying a model that distinguishes rational, intuitive and political decision-making dimensions, the interactions among these dimensions in innovation decision-making in R&D, and the contingency of these dimensions upon the innovation phase. It calls for further research into the contingent nature of innovation decision-making processes.

For practitioners this study has two relevant insights. First it highlights the importance and usefulness of intuitive and political decision-making in addition to the prevailing emphasis on rational decision-making. Second, practitioners may be more alert to consciously changing their dominant decision-making approach across the phases of the innovation process. Third, companies may adjust their human resource policies to this study’s findings.

The literature on rational, intuitive and political decision-making is quite extensive. However, research has hardly studied how these decision-making dimensions develop in conjunction, and over time. This paper reports on a first study to do so and finds that the dominant use of these dimensions is contingent upon the phase of the R&D process and on the decision-making dimensions used in earlier phases. The study suggests that using a contingency approach can help to further integrate the debate in research and practice.

The purpose of this paper is to understand, which internal processes (mental, emotional, cultural, ethical and spiritual) Afghan business leaders use when making managerial decisions.

Primary data were collected through 1-h face-to-face interviews with Afghan business leaders. Interviews were conducted through open-ended questions in a semi-structured format. This method was considered most appropriate to acquire an understanding of senior executives’ interpretation and usage of decision-making processes. The method of analyzing data was thematic analysis where the researchers identified common themes, topics, ideas and patterns of meaning that come up repetitively. The objective of the analysis was to determine the most frequent decision-making processes by business leaders and the reasons for using these processes.

Although the usage of internal processes in decision-making are not homogeneous among Afghan business leaders, some of the processes are used more frequently than others such as mental, cultural and ethical processes. During the mental process of decision-making, the majority of leaders use intuitional decision-making, the minority using logic. Regarding the cultural dimension, the majority of leaders stated that they have an open, friendly, caring organization for each employee and horizontal culture in their organization. The minority indicated that they have a friendly culture but they also considered the processes and hierarchy in their organization. Considering the ethical process of decision-making, leaders stated that their priorities are more ethical than getting extra profit. They believe that profit will be generated while considering ethical values. As a leader noted: when you consider ethics and fulfill your obligations, the profit automatically generates. Most leaders use the internal process of emotion in their decision-making, but the usage has not been frequent. The emotional process of decision-making is more involved when the human factor is involved. For instance, one of the participants stated “I did not fire an employee that I had to because he was a needy and poor person.” About the spiritual process of decision-making, although all leaders agreed that they have used spirituality in decision-making, its usage varies. About one-third of the leaders mostly rely on spirituality or on religious teachings during the decision-making process, one-third somehow rely on spirituality or religion, about 50% of the time and one-third rely on spirituality between 25% to 30% of the time.

This study is pilot research as no previous research was carried out on this topic, therefore, it provides a basis of literature on the usage of internal processes on decision-making in Afghanistan. The findings may differ in other economic and national contexts.

This paper examines the relationship between marketing automation emergence and the marketers' use of heuristics in their decision-making processes. Heuristics play a role for the integration of human decision-making models and automation in augmentation processes, particularly in marketing where automation is widespread.

This study analyzes qualitative data about the impact of marketing automation on the scope of heuristics in decision-making models, and it is based on evidence collected from interviews with twenty-two experienced marketers.

Marketers make extensive use of heuristics to manage their tasks. While the adoption of new automatic marketing tools modify the task environment and field of use of traditional decision-making models, the adoption of heuristics rules with a different scope is essential to defining inputs, interpreting/evaluating outputs and control the marketing automation system.

The paper makes a contribution to research on the relationship between marketing automation and decision-making models. In particular, it proposes the results of in-depth interviews with senior decision makers to assess the impact of marketing automation on the scope of heuristics as decision-making models adopted by marketers.

Managers are increasingly looking to adopt the Internet of Things (IoT) to include the vast amount of big data generated in their decision-making processes. The use of IoT might yield many benefits for organizations engaged in civil infrastructure management, but these benefits might be difficult to realize as organizations are not equipped to handle and interpret this data. The purpose of this paper is to understand how IoT adoption affects decision-making processes.

In this paper the changes in the business processes for managing civil infrastructure assets brought about by IoT adoption are analyzed by investigating two case studies within the water management domain. Propositions for effective IoT adoption in decision-making processes are derived.

The results show that decision processes in civil infrastructure asset management have been transformed to deal with the real-time nature of the data. The authors found the need to make organizational and business process changes, development of new capabilities, data provenance and governance and the need for standardization. IoT can have a transformative effect on business processes.

Because of the chosen research approach, the research results may lack generalizability. Therefore, researchers are encouraged to test the propositions further.

The paper shows that data provenance is necessary to be able to understand the value and the quality of the data often generated by various organizations. Managers need to adapt new capabilities to be able to interpret the data.

This paper fulfills an identified need to understand how IoT adoption affects decision-making processes in asset management in order to be able to achieve expected benefits and mitigate risk.

This paper aims to develop a conceptual framework on how the representativeness heuristic operates in the decision-making process. Specifically, the authors unbundle representativeness into its building blocks: search rule, stopping rule and decision rule. Furthermore, the focus is placed on how individual-level cognitive and behavioral factors, namely experience, intuition and overconfidence, affect the functioning of this heuristic.

From a theoretical standpoint, the authors build on dual-process theories and on the adaptive toolbox view from the “fast and frugal heuristics” perspective to develop an integrative conceptual framework that uncovers the mechanisms underlying the representativeness heuristic.

The authors’ conceptualization suggests that the search rule used in representativeness is based on analogical mapping from previous experience, the stopping rule is the representational stability of the analogs and the decision rule is the choice of the alternative upon which there is a convergence of representations and that exceeds the decision maker's aspiration level. In this framework, intuition may help the decision maker to cross-map potentially competing analogies, while overconfidence affects the search time and costs and alters both the stopping and the decision rule.

The authors develop a conceptual framework on representativeness, as one of the most common, though still poorly investigated, heuristics. The model offers a nuanced perspective that explores the cognitive and behavioral mechanisms that shape the use of representativeness in decision-making. The authors also discuss the theoretical implications of their model and outline future research avenues that may further contribute to enriching their understanding of decision-making processes.

This paper aims to add to the theorization of family dynamics and women’s entrepreneurship by examining women’s influence on decision-making in family businesses. Business decisions in family firms, in particular, are not free from family influence in terms of goals and strategies, and the role of women in decision-making processes is of particular interest. Consequently, the role of women entrepreneurs in family firms and their influence on business development requires a more fine-grained analysis of the family dynamic within the family and the business.

This study draws on a qualitative study and focuses on the life story narratives of nine women in rural family businesses in rural communities of Småland province in Sweden to empirically examine the decision-making processes. This region is known both for its entrepreneurial culture and traditional gender order. Based on the narrative accounts of women entrepreneurs in family businesses, the data analysis method is thematic, using a Gioia-inspired method.

The complexity of decision-making in rural family firms is further complicated in part due to a closeness with the rural community. Thus, a typology of three decision-making modes in family firms emerges an informal family-oriented mode, a semistructured family/employee consensus mode and a formal board mode with at least one nonfamily member. Moreover, the advantages, disadvantages and strategies that women use to influence decisions within the respective mode are outlined.

This work contributes to the study of women’s agency and its implications in family business and entrepreneurship in the rural context. The study implies that women’s agency shapes the (rural) entrepreneurship context and, likewise, the (rural) entrepreneurship context influences women’s agency. Hence, the author challenges the view of women as only caregivers and sheds light on the practices and processes behind the scenes of entrepreneurial family businesses.

This paper aims to identify ethical challenges of using artificial intelligence (AI)-based accounting systems for decision-making and discusses its findings based on Rest's four-component model of antecedents for ethical decision-making. This study derives implications for accounting and auditing scholars and practitioners.

This research is rooted in the hermeneutics tradition of interpretative accounting research, in which the reader and the texts engage in a form of dialogue. To substantiate this dialogue, the authors conduct a theoretically informed, narrative (semi-systematic) literature review spanning the years 2015–2020. This review's narrative is driven by the depicted contexts and the accounting/auditing practices found in selected articles are used as sample instead of the research or methods.

In the thematic coding of the selected papers the authors identify five major ethical challenges of AI-based decision-making in accounting: objectivity, privacy, transparency, accountability and trustworthiness. Using Rest's component model of antecedents for ethical decision-making as a stable framework for our structure, the authors critically discuss the challenges and their relevance for a future human–machine collaboration within varying agency between humans and AI.

This paper contributes to the literature on accounting as a subjectivising as well as mediating practice in a socio-material context. It does so by providing a solid base of arguments that AI alone, despite its enabling and mediating role in accounting, cannot make ethical accounting decisions because it lacks the necessary preconditions in terms of Rest's model of antecedents. What is more, as AI is bound to pre-set goals and subjected to human made conditions despite its autonomous learning and adaptive practices, it lacks true agency. As a consequence, accountability needs to be shared between humans and AI. The authors suggest that related governance as well as internal and external auditing processes need to be adapted in terms of skills and awareness to ensure an ethical AI-based decision-making.

Because of the significant differences in the features and requirements of specific products and the capabilities of various additive manufacturing (AM) solutions, selecting the most appropriate AM technology can be challenging. This study aims to propose a method to solve the complex process selection in 3D printing applications, especially by creating a new multicriteria decision-making tool that takes the direct certainty of each comparison to reflect the decision-maker’s desire effectively.

The methodology proposed includes five steps: defining the AM technology selection decision criteria and constraints, extracting available AM parameters from the database, evaluating the selected AM technology parameters based on the proposed decision-making methodology, improving the accuracy of the decision by adopting newly proposed weighting scheme and selecting optimal AM technologies by integrating information gathered from the whole decision-making process.

To demonstrate the feasibility and reliability of the proposed methodology, this case study describes a detailed industrial application in rapid investment casting that applies the weightings to a tailored AM technologies and materials database to determine the most suitable AM process. The results showed that the proposed methodology could solve complicated AM process selection problems at both the design and manufacturing stages.

This research proposes a unique multicriteria decision-making solution, which employs an exclusive weightings calculation algorithm that converts the decision-maker's subjective priority of the involved criteria into comparable values. The proposed framework can reduce decision-maker's comparison duty and potentially reduce errors in the pairwise comparisons used in other decision-making methodologies.