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This paper aims to explore how the maieutic role of management accounting (MA) can be sustained in the context of MA digitalization.

The paper begins with practitioners’ descriptions of the context that makes the MA support of non-routine decisions maieutic. To understand how the maieutic characteristics can be sustained in future MA digitalization, the authors then analyze the discourses these practitioners have about artificial intelligence (AI) in providing MA support.

As a basis, the authors’ data show various maieutic characteristics within the use of MA answers in decision-making as well as within the MA process of generating such answers. The paper then identifies three MA digitalization discourses, namely, “computation,” “judgment” and human-AI “interaction” discourse, each with their unique agendas on how AI should be used.

The paper is based on the premises that AI and digitalization are often discussed without sufficient understanding about the context being digitalized. The authors’ data suggest that MA support in non-routine decision-making is fundamentally maieutic, and AI – as it currently stands – is not expected to change this by providing perfect answers. The authors provide novel insights about maieutic MA support and the current discourses on using AI in MA support, and how digitalization does not necessarily compromise maieutic MA support but instead has the potential to sustain or even enhance it.

The strategic management literature emphasizes the concept of business intelligence (BI) as an essential competitive tool. Yet the sustainability of the firms’ competitive advantage provided by BI capability is not well researched. To fill this gap, this study attempts to develop a model for successful BI deployment and empirically examines the association between BI deployment and sustainable competitive advantage. Taking the telecommunications industry in Malaysia as a case example, the research particularly focuses on the influencing perceptions held by telecommunications decision makers and executives on factors that impact successful BI deployment. The research further investigates the relationship between successful BI deployment and sustainable competitive advantage of the telecommunications organizations. Another important aim of this study is to determine the effect of moderating factors such as organization culture, business strategy, and use of BI tools on BI deployment and the sustainability of firm’s competitive advantage.

This research uses combination of resource-based theory and diffusion of innovation (DOI) theory to examine BI success and its relationship with firm’s sustainability. The research adopts the positivist paradigm and a two-phase sequential mixed method consisting of qualitative and quantitative approaches are employed. A tentative research model is developed first based on extensive literature review. The chapter presents a qualitative field study to fine tune the initial research model. Findings from the qualitative method are also used to develop measures and instruments for the next phase of quantitative method. The study includes a survey study with sample of business analysts and decision makers in telecommunications firms and is analyzed by partial least square-based structural equation modeling.

The findings reveal that some internal resources of the organizations such as BI governance and the perceptions of BI’s characteristics influence the successful deployment of BI. Organizations that practice good BI governance with strong moral and financial support from upper management have an opportunity to realize the dream of having successful BI initiatives in place. The scope of BI governance includes providing sufficient support and commitment in BI funding and implementation, laying out proper BI infrastructure and staffing and establishing a corporate-wide policy and procedures regarding BI. The perceptions about the characteristics of BI such as its relative advantage, complexity, compatibility, and observability are also significant in ensuring BI success. The most important results of this study indicated that with BI successfully deployed, executives would use the knowledge provided for their necessary actions in sustaining the organizations’ competitive advantage in terms of economics, social, and environmental issues.

This study contributes significantly to the existing literature that will assist future BI researchers especially in achieving sustainable competitive advantage. In particular, the model will help practitioners to consider the resources that they are likely to consider when deploying BI. Finally, the applications of this study can be extended through further adaptation in other industries and various geographic contexts.

Traditional definitions of decision support systems emphasise their support role in individual decision making and utilise notions of rational choice. By considering decisions as an organisational activity, the interpretation of decision support systems use in organisations can move beyond this technical rational understanding, to include potential political and legitimating roles for these systems. These three possible interpretations are discussed in relation to the implementation of a large decision support system in a local government context described by Dutton (1981). In its technical role, the system was used as part of a rational planning agenda. However, the system was clearly also used politically, to promote particular interests and as a lever in negotiations between various groups. Part of the appeal of the decision support system was the appearance of rationality and technical neutrality that it gave to the planning and decision making process, and the legitimation it provided with external constituents. The paper concludes that an unquestioning acceptance of the technical received view of decision support system use is limiting, and that a more reflective approach to their development, implementation and use is required.

The primary purpose is to present empirical measures of variables relating to practices engaged in by site‐based teams, and then to use these variables to test a model predicting significant outcomes of site‐based decision making. The practice variables of site‐based management (SBM) teams are essential in promoting research within a distributed leadership framework.

A path model is computed to test the relationships between factors relating to the support received by site‐based teams; site team communication and decision‐making practice, and perceived outcomes of SBM. Measures are based on survey data collected from 367 team members in 50 schools from fifteen school districts in a northeastern state in the US.

Results show that different factors relating to the support provided to site‐based teams and practices employed by these teams emerge as statistically significant predictors of various outcomes. Results suggest that the resources provided to support site teams, e.g. the devolution of decision‐making power, results in enhanced stakeholder influence, but whether this influence results in better decisions or improvement in teaching and learning depends on the communication and decision‐making practices site teams employ within a distributed leadership framework.

This study sought to identify site team decision making and communication processes that reflect how site teams conduct their work, defining how members of site teams perceive the “rules of the game.” In doing so, it offers a new and different perspective on how such processes impact outcomes associated with shared decision‐making processes, and thus a better understanding of the complex dynamics of school‐site decision making and the distribution of leadership in schools.

Decision support (DS), as a traditional management concept, have had a remarkable role in competitiveness or survival of organizations and nowadays, business intelligence (BI), as a brand modern impression, has various contributions in supporting decision-making process. Although, a variety of benefits are expected to arise from BI functions, researches, and models that determining the effect of BI functions on the decisional and organizational benefits are rare. The purpose of this paper is to study the relationship between BI functions, DS benefits, and organizational benefits in context of decision environment.

This research conducts a quantitative survey-based study to represent the relationship between BI capabilities, decision support benefits, and organizational benefits in context of decision environment. On this basis, the partial least squares (PLS) technique employs a sample of 228 firms from different industries located in Middle-East countries.

The findings confirm the existence of meaningful relationship between BI functions, DS benefits, and organizational benefits by supporting 15 out of 16 main hypotheses. Essentially, this research provides an insightful understanding about which capabilities of BI have strongest impact on the outcome benefits.

The results can provide effective and useful insights for investors and business owners to utilize more appropriate BI tools and functions to reach more idealistic organizational advantages. Also it enables managers to better understand the application of BI functions in the process of achieving the specified managerial support benefits.

The purpose of the chapter is to study the possibilities of systemic intellectual support for managerial decisions in modern business systems and perspectives of authomatization of this process on the basis of intellectual technologies.

The methodology of the chapter includes the methods of systemic and problem analysis, analysis of causal connections, modeling, and formalization.

Advantages of usage of technologies of intellectual support for decisions in modern business systems are substantiated; they are connected to multitask character, full determination of possibilities and problems of the business system regardless of employees’ involvement in this process, and “scale effect” during making of managerial decisions. Also, drawbacks of intellectual support for decision-making in modern business systems are determined: incompleteness of authomatization of the process of making of managerial decision, foundation primarily on digital data, necessity for complex digitization of the business system, and the problem of security of digital data and intellectual technologies.

Large opportunities of systemic intellectual support for managerial decisions in modern business systems and wide perspectives of almost full authomatization of this process on the basis of intellectual technologies, accessible at all stages of the process of decision-making, are determined. For this, an algorithm of complex intellectual support for decisions in a modern business system is offered. The obtained results allow determining intellectual technologies of support for managerial decisions in modern business systems as a perspective direction of improving this process.

According to the social justice model of disability, inclusion is about securing civil and human rights for individuals with disabilities. To that end, supported decision-making is a person-centred process that allows individuals to take control of their own choices and increases their ability to live self-determined lives. Utilizing a case-study approach, this chapter examines the differences between guardianship and supported decision-making and explores how one individual who had been placed within a guardianship format, embraced a more supported decision-making framework through self-selecting a group of family, friends and professionals to serve in an advisory capacity. Through this approach, he regained control of decision-making, assumed the ‘dignity of risk’ associated with decision-making and restored his right to self-determination.

The existing literature expresses a strong need to develop tools that support the manufacturing reshoring decision-making process. This paper aims to examine the suitability of analytical hierarchy process (AHP)-based tools for initial screening of manufacturing reshoring decisions.

Two AHP-based tools for the initial screening of manufacturing reshoring decisions are developed. The first tool is based on traditional AHP, while the second is based on fuzzy-AHP. Six high-level and holistic reshoring criteria based on competitive priorities were identified through a literature review. Next, a panel of experts from a Swedish manufacturing company was involved in the overall comparison of the criteria. Based on this comparison, priority weights of the criteria were obtained through a pairwise analysis. Subsequently, the priority weights were used in a weighted-sum manner to evaluate 20 reshoring scenarios. Afterwards, the outputs from the traditional AHP and fuzzy-AHP tools were compared to the opinions of the experts. Finally, a sensitivity analysis was performed to evaluate the stability of the developed decision support tools.

The research demonstrates that AHP-based support tools are suitable for the initial screening of manufacturing reshoring decisions. With regard to the presented set of criteria and reshoring scenarios, both traditional AHP and fuzzy-AHP are shown to be consistent with the experts' decisions. Moreover, fuzzy-AHP is shown to be marginally more reliable than traditional AHP. According to the sensitivity analysis, the order of importance of the six criteria is stable for high values of weights of cost and quality criteria.

The limitation of the developed AHP-based tools is that they currently only include a limited number of high-level decision criteria. Therefore, future research should focus on adding low-level criteria to the tools using a multi-level architecture. The current research contributes to the body of literature on the manufacturing reshoring decision-making process by addressing decision-making issues in general and by demonstrating the suitability of two decision support tools applied to the manufacturing reshoring field in particular.

This research provides practitioners with two decision support tools for the initial screening of manufacturing reshoring decisions, which will help managers optimize their time and resources on the most promising reshoring alternatives. Given the complex nature of reshoring decisions, the results from the fuzzy-AHP are shown to be slightly closer to those of the experts than traditional AHP for initial screening of manufacturing relocation decisions.

This paper describes two decision support tools that can be applied for the initial screening of manufacturing reshoring decisions while considering six high-level and holistic criteria. Both support tools are applied to evaluate 20 identical manufacturing reshoring scenarios, allowing a comparison of their output. The sensitivity analysis demonstrates the relative importance of the reshoring criteria.

This chapter focuses on techniques and technologies to aid groups in making decisions, with an emphasis on computer-based support. Many office workers regularly meet colleagues and clients in virtual meetings using videoconferencing platforms, which enable participants to carry out tasks in a manner similar to a face-to-face meeting. The development of computer-based platforms to facilitate group tasks can be traced back to the 1960s, and while they support group communication, they do not directly support group decision making. In this chapter we distinguish four technologies developed to provide support to group decisions, clustered into two main traditions. Technologies in the task-oriented tradition are mainly concerned with enabling participants to complete tasks to solve the group's decision problem via computer-supported communications. Group Decision Support Systems and social software technologies comprise the task-oriented tradition. Alternately, in the model-driven tradition, participants use computers to build and use a model that acts as a referent to communicate, mostly verbally, about the group's decision problem. System modeling and decision-modeling technologies constitute the model-driven tradition. This chapter sketches the history and guiding ideas of both traditions, and describes their associated technologies. The chapter concludes with questioning if increased availability of online tools will lead to increased use of group decision support technologies, and the differential impact of communication support versus decision support.

Design-Build (DB) is known as the alternative for Design-Bid-Build in the Malaysian construction industry. For DB projects, it is critical to adopt effective decision support tool to ensure the execution of a systematic decision-making technique. This study aimed to examine the impact of a decision support tool for novice decision makers to reject or adopt DB for their construction projects.

Literature review and qualitative input from experts identified several key-selection factors pertaining to critical success factors and design-build drivers. This resulted in the development of Decision Support Tool for Design-Build (DST-DB). A quasi-experiment, which involved 382 novice decision makers in the construction industry, was conducted to test the DST-DB quantitatively. The participants were required to compare two construction projects using DST-DB and traditional decision-making methods. Multivariate analysis was performed to analyse all collected data.

The quasi-experiment data suggests that DST-DB enables significantly higher usability, likelihood, precision, confidence and satisfaction rate when compared to the traditional decision-making process. The pre- and post-surveys indicated that the DST-DB is effective in improving decision-making performance through selection factors of client-briefing, maximised resources and sharing expertise. The participants also agreed that DST-DB is easy to use and helps them to gain better understanding of the decision-making process for construction projects.

This research contributes to the existing body of knowledge through the impact of DST on the decisions of novices. The novice decision makers found that DST-DB is practically adaptable and comparatively effective for decision-making process than traditional decision-making methods. This contributes to the practical application of construction companies to provide DST-DB training to the fresh graduate employees to enhance their competencies in the decision-making process.