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This paper aims to offer an incremental contribution, augmenting the notion of situated rationality as proposed by terBogt and Scapens (2019). Through insights from empirical data, the authors explore the role of situated rationalities of key individual actors in processes of management control change.

A qualitative research approach was adopted with qualitative data collected in a single public service organisation through face-to-face interviews, organisation documentation and observations.

The findings present the important role of key individual actors in bringing about a new situated rationality in a housing department. External austerity forces combined with actors’ experience rationalities acted as a stimulus to change existing management control practices in the management of public services.

The paper conceptualises “experience” rationality, capturing the experiences of a key actor, including elements of leadership style. Drawing on a story of a complex process of management control change, this paper thus reveals interactions between generalised practices and situated rationalities which were not highlighted by the extended framework of terBogt and Scapens.

This study aims to investigate whether objective and subjective rationality affects individual voters’ use of accounting information and if such use affects voting behavior. While prior accounting studies assume voter rationality concerning financial performance and political outcomes, this study distinguishes between two types of voters: objective rational voters (who make voting decisions about multiple alternatives based on objective information) and subjective rational voters (who make decisions based on their subjective values, and thus do not explore information or explore only information biased toward one alternative). This study expects that accounting information can influence the voting behavior of objective and subjective rational voters.

Focusing on the 2020 Osaka Metropolitan Plan Referendum, this study used an online survey conducted on 768 respondents after the referendum.

This study finds that objective rational voters use accounting information more than subjective rational voters, voters who used accounting information were more likely to vote against the referendum, and voting behavior is not directly affected by the type of rationality of voters; rather, objective rational voters are more likely to use accounting information that has a mediating effect on voting behavior.

The results advance the understanding of public sector accounting research and practices by providing evidence of the individual voter’s use of accounting information and their voting behavior in political contexts.

The purpose of this paper is to test whether financial analysts’ rationality in making stocks’ earnings forecasts is homogenous or not across different information regimes in stocks’ past returns.

By treating stocks’ past returns as the information variable in this study, the authors employ a threshold regression model to capture and test threshold effects of stocks’ past returns on financial analysts’ rationality in making earnings forecasts in different information regimes.

The results show that three significant structural breaks and four respective information regimes are identified in stocks’ past returns in the threshold regression model. Across the four different information regimes, financial analysts react to stocks’ past returns quite differently when making one-quarter ahead earnings forecasts. Furthermore, the authors find that financial analysts are only rational in a certain information regime of stocks’ past returns depending on a certain return-window such as one-quarter, two-quarter or four-quarter time period.

This study is different from those in the existing literature by arguing that there could exist heterogeneity in financial analysts’ rationality in making earnings forecasts when using stocks’ past returns information. The finding that financial analysts react to stocks’ past returns differently in the different information regimes of past returns adds value to the research on financial analysts’ rationality.

As China embarks upon a new era of high-quality development, it is increasingly important and imperative for China’s economic development to live up to its real nature, which is to satisfy people’s growing needs for a better life. The paper aims to discuss this issue.

The paper attempts to discuss the implication of HQD and its related theoretical issues from the basic theory of economics, and literature review. It is necessary to return to Marx’s “dual character of commodity” to check the theoretical foundation of this issue, based on the duality methodology, namely, the duality of the value of use and the value of exchange.

Moving from HSG phase to HQD phase constitutes a major challenge and an arduous task that is extremely difficult both theoretically and practically. A series of new problems crop out as to the theoretical understanding and practical resolution. Fundamentally speaking, this new dynamic mechanism intrinsically requires a perfect integration of the instrumental rationality of market economy and the value-based rationality of economic development.

This new momentum requires a perfect match between the instrumental rationality of market economy and the value-based rationality of economic development.

Entrepreneurs are increasingly relying on artificial intelligence (AI) to assist in creating and scaling new ventures. Research on entrepreneurs’ use of AI algorithms (machine learning, natural language processing, artificial neural networks) has focused on the intra-organizational implications of AI. The purpose of this paper is to explore how entrepreneurs’ adoption of AI influences their inter- and meta-organizational relationships.

To address the limited understanding of the consequences of AI for communities of entrepreneurs, this paper develops a theory to explain how AI algorithms influence the micro (entrepreneur) and macro (system) dynamics of entrepreneurial ecosystems.

The theory’s main insight is that substituting AI for entrepreneurial ecosystem interactions influences not only entrepreneurs’ pursuit of opportunities but also the coordination of their local entrepreneurial ecosystems.

The theory contributes by drawing attention to the inter-organizational implications of AI, explaining how the decision to substitute AI for human interactions is a micro-foundation of ecosystems, and motivating a research agenda at the intersection of AI and entrepreneurial ecosystems.

In response, the purpose of this paper is to provide theoretical frameworks about the organizational uncertainty behind what and when to adopt blockchain technology and their implications on transaction costs. The immature nature and the absence of standards in blockchain technology lead to uncertainty in government organizations concerning the adoption (“what to adopt”) and the identification of the right time (“when to start”).

Using transaction cost theory and path dependency theory, this paper proposes two frameworks: to assess transaction cost risks and opportunities costs; and to depict four different types of transaction costs outcomes regarding blockchain adoption.

This paper identifies various theoretical concepts that influence blockchain adoption and combine the two critical constructs of “bounded rationality” and the “lock-in effect” to categorize the multiple transaction costs outcomes for blockchain adoption.

Although existing research in blockchain highlights mainly the potential benefits of blockchain applications, only a little attention has been given to frameworks that categorize potential transaction costs outcomes under uncertainty, in particular from organizational theorists.

Both frameworks advance the understanding of the decision-making behind blockchain adoption and synthesize the current literature to offer conceptual clarity regarding the varied implications and outcomes linked to the uncertainty regarding transactions costs stemming from blockchain technology.

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.

Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.

Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.

The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

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.

This paper aims to identify and analyze the agtech classification and categorization systems in the Brazilian context.

The systematic literature review (SLR) was carried out according to the protocol of Kitchenham and Charters (2007). The classification systems found in literature were evaluated using the thinking aloud protocol, as proposed by Ericsson and Simon (1993). The responses obtained were evaluated through lexicographic analysis, described by Bécue-Bertaut (2019) and content analysis, described by Bardin (2011).

SLR identified four agtech classification systems. The model proposed by Dias, Jardim, and Sakuda (2019) was the one with the highest adherence to classify Brazilian agtechs. From the analysis of the systems found in literature, the authors proposed a new categorization model of agricultural startups (agtechs).

The study has limitations in relation to the theoretical and empirical validation of the model proposed by the authors. This limitation can be the subject of subsequent research.

The SLR study considers the evolution of the classification systems of a new agribusiness reality, the agtechs. In addition, there is a practical contribution in proposing a new classification system that attempts to address some of the limitations found in previous studies.

Agtechs are startups focused on developing solutions for agriculture and have shown a significant increase in recent years. However, there are few studies focused on this type of company. Even rarer are the studies that seek to classify and categorize them. The present work opens the horizon for future studies focused on this new reality.

The core of the micro–macro paradigm of mainstream Western economics is the assumption that a rational economic man with complete freedom of economic behaviors living in a fully competitive, free-market economy pursues maximum personal benefits. The purpose of this paper is to show the reasons for failure of mainstream Western economics explaining the “mystery of China’s economic growth” and the necessity of understanding the mystery from the paradigm of realm economics.

The system of socialism with Chinese characteristics led by the Communist Party of China (CPC) and the local governments that play a crucial role in the reform and opening-up has the realm attribute. It is necessary to develop a new paradigm for realm economic analysis and promote the creation of new economic globalization and international political and economic order.

According to the fourth plenary session of the 19th CPC Central Committee, “Since the New China was founded 70 years ago, our Party has led our people to create the rarely-seen miracle of rapid economic development and miracle of long-term social stability”. The authors find that it is effective and necessary to explain the miracle of China’s economic growth from the paradigm of realm economics.

As proven by practice, the system of socialism with Chinese characteristics and the governance system of China are guided by Marxism, rooted in China with a deep Chinese cultural foundation, and sincerely supported by the people.