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How do cognitive aspects influence the use/non-use of accounting information by the politicians? The purpose of this paper is to conceptualize and theorize the readiness to use and the actual use of accounting information in relation to the human and social agency involved.

Applying cognitive fit theory and social cognitive theory, the authors explain how cognition of accounting information producers and users relates to their tasks and their environment. Analyzing cognitive matching, the authors develop accounting information usefulness as a function of the cognitive match between the accounting information producers and users.

The theoretical findings posit that cognitive fit increases with the degree of matching between the cognition of accounting information producers and the cognition of accounting information users. The theory proposes that enriching and matching the various cognitive factors lead to formation of more aligned mental representations to govern the processes of accounting information production and use as a prerequisite for the accounting information usefulness.

By theorizing human cognition, behavior and learning, the authors seek to contribute to the explanation and prediction of accounting information use. Future research needs to empirically validate and/or further develop the propositions.

Practically, the conceptualization can be used to align individual and collective learning on both sides and to introduce information use audit as an instrument for supporting collective learning.

The theory of accounting information usefulness is the first attempt in public sector accounting literature to explain the relation of production and consumption of accounting information in relation to the cognition of the actors involved.

Although not yet frequently used in marketing management, design thinking (DT) encompasses a creative, proactive, and empathic approach that connects different bodies of knowledge to shape innovative product and service solutions. Based on lean progress models, DT combines a manufacturer’s strategic objectives with the customer’s business requirements. This model focusses on the most important ‘pains’ the customers actually have in order to co-develop and more successfully sell products or services that provide value to specific customer groups or segments. This chapter aims to shed light on the potential of applying DT in new product or service development processes in different business fields to incorporate significant customer requirements a priori. The goal of this method is twofold: to reduce the extremely high risk of unsuccessful product launches and to make the integration of important customers during the product development phase easier.

This paper aims to provide a promising memetic algorithm (MA) for an unrelated parallel machine scheduling problem with grey processing times by using a simple dispatching rule in the local search phase of the proposed MA.

This paper proposes a MA for an unrelated parallel machine scheduling problem where the objective is to minimize the sum of weighted completion times of jobs with uncertain processing times. In the optimal schedule of the problem’s single machine version with deterministic processing time, the machine has a sequence where jobs are ordered in their increasing order of weighted processing times. The author adapts this property to some of their local search mechanisms that are required to assure the local optimality of the solution generated by the proposed MA. To show the efficiency of the proposed algorithm, this study uses other local search methods in the MA within this experiment. The uncertainty of processing times is expressed with grey numbers.

Experimental study shows that the MA with the swap-based local search and the weighted shortest processing time (WSPT) dispatching rule outperforms other MA alternatives with swap-based and insertion-based local searches without that dispatching rule.

A promising and effective MA with the WSPT dispatching rule is designed and applied to unrelated parallel machine scheduling problems where the objective is to minimize the sum of the weighted completion times of jobs with grey processing time.

This paper aims at proposing knowledge translation as an element of business model design that can support entrepreneurs in achieving alignment and collaboration between entrepreneurial teams and external stakeholders.

The conceptual model presented in the paper is developed from the literature review and draws mainly on two streams of work as follows: first, the contributions related to the lean start-up methodology initially developed by Blank and Ries and second, the work of Osterwalder and Pigneur on business models and its subsequent developments. In addition, we draw on key insights from the entrepreneurship and organizational learning literature, such as discovery-driven planning and disciplined entrepreneurship.

The continuous validation framework (CVF) is introduced, posing the attention on underlining knowledge-translation mechanisms to decode complex concepts related to new venture creation.

The authors propose a new framework (the CVF) as an effective translational tool because it is a visual diagram that allows entrepreneurs to translate complex and technical ideas into a format that is more understandable for external audiences. Additionally, for each step of the CVF, specific translational mechanisms are defined and discussed, as each stage of the CVF presents specific translational challenges that result in outcomes that differ from stage to stage.

The purpose of this paper is to link firms’ strategic archetypes as formulated by Miles and Snow (1978) to the more recent literature on organizational ambidexterity. Examining these obvious linkages, the paper also addresses how these firms address their entrepreneurial, engineering and administrative problem domains in relationship with the firm’s strategic archetype.

Data were collected from 503 firms across the US. Measures previously validated were used to collect information related to the strategic archetype as well as the three problem domains. Multiple discriminant and regression analyses were used to test the hypotheses.

Most of the hypotheses relating the entrepreneurial (exploration and exploitation), engineering (radical and incremental innovation) and administrative problem (adaptation and alignment) to the four strategic archetypes (defender, prospector, analyzer and reactor) were supported. Additionally, the authors found that the firms that had the closest alignment along the three problem domains outperformed the other firms.

Although the Miles and Snow typology has received considerable research attention, the obvious links with more contemporary research on organizational ambidexterity has been neglected. Through this integration, with more recent key strategic management concepts, this paper shows the utility and current relevance of the Miles and Snow archetypes.

This paper aims to propose an integrated methodology for evaluating academic spin-offs (ASOs) for supporting both the development phase and performance evaluation. The ASOs have peculiar characteristics compared to other start-up companies and the debate on their evaluation is still open.

The proposed methodology, adopting a lean approach, faces the typical problems that characterize the growth of an ASO: the excessive attention to the technological aspects with respect to the commercial and managerial ones; and the need for evaluation systems that try to evaluate all risk areas and to highlight any misalignment. The methodology was built also starting from the results of an Erasmus + research project, co-funded by the European Commission, called spin-off lean acceleration.

The methodology proposes to monitor the main risk areas (market, technological, implementation, governance and financial). For each of these areas, at first, a framework and a checklist are proposed for supporting the qualitative assessment of the potential of each areas. In the second part, a set of metrics for monitoring the performances and to understand if the spinoff is developing in the right direction is proposed. Moreover, the methodology was applied to the spin-offs at the University of Calabria (Italy), and the paper reports the first results obtained.

A new canvas model (lean acceleration canvas), more specific and suited to the context of ASOs, was developed and tested. A lean approach has been adopted also for understanding the weakness of traditional methods. The proposed methodology could be used by the technology transfer offices in their institutional activity of supporting ASOs.

The purpose of this research study is to empirically investigate the Figma prototyping technology adoption factors among entrepreneurship and innovation libraries for providing support to startups by developing and evolving the prototype solutions in collaboration with health libraries.

This study uses the technology adoption model (TAM) as a framework and the partial least squares structural equation modeling (PLS-SEM) method of structural equation modeling (SEM) using SmartPLS 3.2.9 software version to investigate the prototyping adoption factors among entrepreneurship and innovation libraries for rural health innovations. A total of 40 libraries, spread over 16 entrepreneurship and innovation libraries, participated in this survey, including participants from Europe (35%), Asia (15%) and USA (50%).

The findings show that previous experience, social impact, brand image and system quality have a significant positive impact on entrepreneurship and innovation libraries' perceived usefulness (PU) of prototyping technology. Perceived ease of use of prototype technology is positively influenced by usability, training materials and documentation, experience and self-efficacy. Together, perceived usefulness and perceived ease of use have a significant influence on behavioural intention. Behavioural intention is positively impacted by minimal investment and shallow learning curve. Technology adoption is furthered by behavioural intention. The control variables, for instance location, gender and work experience (as librarian), were found not having any impact on Figma technology adoption.

Through strategic partnerships with other libraries (including health libraries), policymakers, and technology providers, the adoption of prototype technology can be further accelerated. The important ramifications for policymakers, technology providers, public and entrepreneurship and innovation libraries to create a self-reliant innovation ecosystem to foster rural health innovation based on entrepreneurship are also listed in the article.

This research is distinctive since it integrates several areas of study, including entre, advances in rural healthcare and libraries. A novel idea that hasn't been thoroughly investigated is the collaboration between entrepreneurship and innovation libraries and health libraries for supporting businesses. This study offers insights into the factors that drive technology adoption and offers practical advice for policymakers and technology providers. It also advances understanding of the adoption of Figma prototyping technology among libraries for rural health innovation. Overall, this study provides a novel viewpoint on the nexus between different disciplines, showing the opportunity for cooperation and innovation in favour of rural health.

The purpose of this paper is to examine the failures of business intelligence (BI) implementations and to understand why they fail as well as what action can be taken to ensure implementation success.

The paper is based on a literature review of academic journals and case studies relating to BI, and the success and failure of the implementation of such projects. It focuses on four areas of BI projects to measure success: return on investment, non-concrete measures, project management measures and user satisfaction. The literature provides insights into what factors contribute to the success of a BI implementation and what factors contribute to the failure. Once the failures can be ascertained, a strategic approach to remedying the failure is discussed.

Implementation failure specifically relating to BI is a rarely discussed topic. This paper provides an understanding of why BI implementations fail and how organisations can ensure, prior to implementing such a solution, the considerations that need to be made to ensure that success is achieved from a technological, organisational and process perspective.

The paper uses empirical evidence from the literature to provide an understanding of why BI implementations fail. The factors contributing to BI failure are examined along with insights into how to succeed with a BI implementation.

This paper aims to investigate the effect of business incubation metrics based on an adaptation of the lean start-up (LS) framework on start-up survival after incubation. This study also analyzes the obstacles in implementing the LS framework as incubation metrics.

This study uses mixed methods. Quantitative research using multiple linear regression was applied to the data of 30 start-ups incubated at Bandung Techno Park for the 2014–2017 period and survival tracking data after the incubation. A qualitative approach to complete the explanatory work was conducted through in-depth interviews with 12 respondents, including start-up graduates from the incubation program, program managers and mentors.

This study confirms that several LS incubation metrics significantly affect start-up sustainability after incubation. In addition, this study also explains several problems in applying the LS discipline that needs attention to increase incubation success.

Research was conducted only at one technology business incubator (TBI) model that focuses on digital start-ups in the emerging ecosystem. Research results can be biased in different situations and ecosystems.

The explanation of the relationship of LS-based incubation metrics to the survival of start-ups, as well as the challenges of their implementation, can be a reference for TBI management to consider and prioritize intervention strategies, thereby improving TBI’s business processes and increasing the success rate of incubated start-ups.

The creation of university start-ups and spin-offs has become a key performance indicator mandatory for technology universities in Indonesia. The existence of TBI institutions in universities as channels of technology commercialization is essential. The incubator’s success in creating a new technology-based company will have a significant social impact on the surrounding environment.

Although the LS method is popular in start-up communities and among practitioners, it is rarely used in the incubation process at universities. These results can be considered for university TBIs to explore LS as an incubation management tool to increase the success rate of incubated start-ups.

Although business incubators are widely used support mechanisms for innovative entrepreneurship, the literature still lacks theoretically based explanations of how the incubation process creates value for stakeholders. This study aims to address this gap by developing a conceptual model, and related research propositions, that explains how the entrepreneurial logic in use by an incubator influences the incubation process (selection criteria and service offering) and performance.

Integrating the effectuation and entrepreneurial opportunities literature, which shares common conceptualizations about how the predictability of the future affects entrepreneurial action, the authors posit two archetypes of entrepreneurial logic that are associated with different incubation processes (causal or effectual) and two archetypes of opportunity attributes (discovery- or creation-based) that affect the incubation process needed to support their development.

Juxtaposing these archetypes, the proposed cross-level conceptual model specifies four levels of fit (ideal, surplus, deficit and mismatch) between the incubation process and the opportunity attributes of individual ventures, which directly influence venture performance (high, moderate and low). In turn, an incubator's performance is largely shaped by the overall performance of ventures in its portfolio.

This paper responds to the call for theory-building that links the antecedents and outcomes of the incubation process across levels of analysis. In addition to developing a conceptual model and research agenda at the intersection of entrepreneurship and business incubation, the proposed model also has implications for incubator directors deciding how to allocate limited resources, and for public/private sector administrators interested in leveraging investment in business incubators.