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This research paper aims to provide a comprehensive overview of the determinants influencing organisations decisions to adopt crowdsourcing. By synthesising existing literature, it seeks to identify critical factors that act as enablers or inhibitors in the adoption process and propose a framework for understanding crowdsourcing adoption within organisational contexts.

This study employed a systematic literature review methodology to examine the determinants influencing organisations' decisions to adopt crowdsourcing. The review encompassed research articles from the Web of Science and Scopus databases, spanning 2006 to 2021. Additionally, morphological analysis was conducted to categorise the identified determinants into three distinct contexts: technological, organisational and environmental. This methodological approach facilitated a comprehensive exploration of the factors shaping crowdsourcing adoption within organisational settings, allowing for a nuanced understanding of the phenomenon across different dimensions.

The study identifies 12 determinants influencing crowdsourcing adoption, categorised into technological, organisational and environmental dimensions. These determinants include technological compatibility, organisational readiness, top management support, crowd readiness and availability of third-party platforms. While some determinants primarily act as enablers, others exhibit dual roles or serve as inhibitors depending on contextual factors.

The findings offer valuable insights for scholars, practitioners, and organisational leaders seeking to leverage crowdsourcing as a strategic tool for innovation and competitiveness. The assessment scale of drivers and barriers developed in this research offers a systematic approach for evaluating the factors influencing crowdsourcing adoption, providing a nuanced understanding of innovation adoption dynamics. Theoretical implications include advancements in morphological analysis methodology and a nuanced understanding of innovation adoption dynamics. Managerial implications highlight strategies for enhancing organisational readiness, leveraging leadership support and mitigating adoption risks. Overall, the study provides a foundation for future empirical research and practical guidance for organisations planning to adopt crowdsourcing initiatives.

This research contributes significantly to crowdsourcing by presenting an integrated and theoretically grounded framework. By consolidating adoption determinants from diverse contexts, this study clarifies the understanding of crowdsourcing adoption. The framework offers practical value to managers and decision-makers, equipping them with a structured approach to assess and navigate the challenges associated with effectively adopting crowdsourcing. As such, this study contributes to advancing crowdsourcing practices and supports more informed managerial decision-making in innovation and knowledge sourcing.

Recent national policy adoptions of the social determinants of health approach present enormous challenges to practitioners designing health promotion programs aimed at eliminating health disparities. This chapter provides a framework for understanding the social determinant rationale embedded in Healthy People 2020 and introduces the concept of place as an important consideration.

This chapter presents a conceptual explanation of social determinant thinking and describes the potential impact for traditional health promotion activities that target the at-risk populations.

Two major resources, the Health Impact Assessment Toolkit and the HHS Disparities Action Plan, have emerged as frameworks for developing a health in all policies approach that will enable health practitioners to enhance their social determinant interventions.

Current social determinant approaches and models need to be strategically tailored to interventions aiming to reduce health disparities. Additional research focusing on how these approaches are integrated within the existing health promotion program frameworks is required.

Very few health practitioners have had the opportunity to integrate a social determinant approach that emphasizes the concept of place and explores the consequences of using a health in all policies approach. This chapter serves as a practical introduction and outlines the major challenges.

The tipping point for the inclusion of social determinants of health in addressing health disparities occurred with the publication of Healthy People 2020. As this innovation begins to diffuse throughout the country, health practitioners will benefit by reviews and applications of the new rationale and model.

This paper examines the profitability and performance measurement of U.S. regional banks during the period 1994–2011, using the GMM estimator technique. Our study extends prior research by including several factors not previously considered using U.S. data.

We use bank-specific, industry-specific, and macroeconomic determinants of profitability contemporaneous with our performance indicators. We follow the accounting fundamental analysis path in explaining the bank performance.

Among the performance measures, the efficiency ratio and provisions for credit losses are negatively and equity scaled by assets is positively related to profitability. However, these relationships either reverse (efficiency ratio and provisions for credit losses) or become insignificant (equity scaled by assets) when the target becomes change in profitability. The level of nonperforming assets is negatively related to profitability across all measures of profitability used. Macroeconomic variables are largely unrelated to profitability during the year they are measured. However, they have a significant relationship with earnings change measures, suggesting they have a lagged effect on profitability. The slope of the yield curve is especially strong in this regard.

We use our determinants to model changes in bank profitability one year ahead, in addition to including several factors not previously considered, using the predictive focus of the fundamental analysis research.

This chapter investigates the social determinants (urbanisation, population, literacy and corruption) of greenhouse gas (GHG) emissions in the top 100 developed and developing emitting countries. The data were collected from central repositories for the different variables explored for the period 2012–2020 in a cross-country analysis. Fixed effects ordinary least squares (OLS) regression was used to analyse the data. The results for all top 100 countries and developing countries show that urbanisation and corruption are significantly positive and negative determinants of GHG emissions, respectively. In addition, literacy is a significant positive determinant of GHG emissions in developing countries but not in the top 100 and developed countries. Population is not significant in the top 100 developed and developing countries. The results for the control variables suggest that primary energy consumption is a positive significant determinant of GHG emissions in the top 100 developed and developing countries. However, gross domestic product (GDP) is not a significant determinant of GHG emissions. The findings have important policy implications.

This chapter intends to contribute to the debate on the determinants of corporate social responsibility (CSR) and their impact on performance measurement and communication systems. It aims at analyzing the relationship between the reasons why firms adopt CSR and the importance given to voluntary CSR disclosure.

Two main categories of CSR determinants have been identified: the external ones, coming from the environment outside the firm, and the internal determinants, which are linked to some specific characteristics of the enterprise and to the objectives it pursues.

The analyzed sample consists of 120 large Italian manufacturing and nonmanufacturing enterprises. The research hypotheses concerning the relationship between external and internal determinants of CSR and CSR disclosure were verified using an independent sample t-test, evaluating the equal variances of clusters using the Levene’s test.

Main results point out that in companies giving importance to CSR disclosure, the internal drivers are more relevant than the external ones in determining the attitude toward CSR. Among the internal determinants, drivers related to company and management values and ethics are quite relevant.

This study is subject to the limitations that generally apply to cross-sectional survey-based research.

Our research findings show that legitimacy theory represents the most relevant theory in explaining CSR disclosure practices of Italian large firms, as well as the operational implementation of stakeholder theory, such as stakeholder management. On the contrary, institutional theory only partially explains CSR disclosure, with respect to the pressures coming from financial markets.

The main purpose of this research is to (1) prioritise key determinants of Industry 4.0 (I4.0) readiness assessment and (2) evaluate causal relationships among those determinants and associated sub-criteria based on inputs from industry experts.

The methodology involved two phases: (1) an MCDM approach for determining causal relationships among determinants and (2) empirical validation of findings from the first phase using industry experts' inputs.

It was found that while the choice of I4.0 technologies is important, organisational factors are also critical, as evidenced by the ranking of the “Strategy and Organisation” determinant as the highest rank prominent determinant. Also, the ranking of the sub-criteria within each determinant shows the importance of several organisational influencing and resulting sub-criteria.

This research extends the existing literature on I4.0 by demonstrating the prioritisation of determinants and delineating causal relationships among them and associated sub-criteria as a basis for developing I4.0 adoption guidelines. This research is limited to the specific scope of determinants selected/considered and experts' inputs from the Sri Lankan manufacturing sector. Future studies could consider extending this research into a broader global manufacturing context.

Prioritisation and causal relationships of I4.0 readiness assessment determinants, supported with inputs from functional managers and industry experts, could be used to guide practitioners in developing guidelines for I4.0 adoption in a phased manner.

This research provides a re-evaluation and validation of a selected I4.0 readiness assessment framework from the perspectives of interdependencies and casual relationships among its determinants and sub-criteria, based on inputs from industry experts as a basis for developing guidelines for I4.0 adoption.

This study aims to investigate whether the model containing five organisational determinants of corporate entrepreneurship developed by Kuratko, Hornsby and Covin is valid in Serbia.

The model was tested on a sample that included managers and employees from four banks in Serbia. The Corporate Entrepreneurship Assessment Instrument (CEAI) was used as the research instrument and factor analysis was used as the basic statistical method. This study examined whether the 48 items that compose the CEAI could be grouped in the context of the national culture of Serbia to provide the five determinants that were identified by Kuratko, Hornsby and Covin.

The results show that the factor analysis identified four determinants identical to those in the CEAI model. However, time availability failed the validity test in previous studies conducted in Serbia and other countries with collectivist cultures. It can be concluded that collectivism connected with high-power distance, uncertainty avoidance and the polychromatic concept of time caused the cultural limitation of time availability as a determinant of corporate entrepreneurship.

This study indicates that national culture could be a factor that determines the validity of organisational determinants of corporate entrepreneurship and that these factors cannot be taken for granted in cultures other than those in which the theory of corporate entrepreneurship arose. Finally, corporate entrepreneurship has been investigated in the banking industry, which is unusual because it is globally renowned for its conservatism.

This study aims to examine the determinants that influence housing prices in Dammam metropolitan area (DMA), Saudi Arabia, by using the analytic hierarchy process (AHP) model. The study considers determinants such as building age (BLD AG), building size (BLD SZ), building condition (BLD CN), access to parking (ACC PK), proximity to transport infrastructure (PRX TRS), proximity to green areas (PRX GA) and proximity to amenities (PRX AM).

The AHP decision model was used to assess the determinants of housing prices in DMA, using a pair-wise comparison matrix to determine the influence of the investigated factors on housing prices.

The study’s results revealed that building size (BLD SZ) was the most critical determinant affecting housing prices in DMA, with a weight of 0.32, trailed by proximity to transport infrastructure (PRX TRS), with a weight of 0.24 as the second most influential housing price determinant in DMA. The third most important determinant was proximity to amenities (PRX AM), with a weight of 0.18.

This study addresses a research gap by using the AHP model to assess the spatial determinants of housing prices in DMA, Saudi Arabia. Few studies have used this model in examining housing price factors, particularly in the context of Saudi Arabia. Consequently, the findings of this study provide unique insights for policymakers, housing developers and other stakeholders in understanding the importance of building size, proximity to transport infrastructure and proximity to amenities in influencing housing prices in DMA. By considering these determinants, stakeholders can make informed decisions to improve housing quality and prices in the region.

Micro, small and medium-sized enterprises are the live wire of construction industry in developing countries. These classes of establishments are most affected by economic contraction and turmoil, thus affecting their performance and survivability. Hence, the purpose of this study is to investigate and prioritize the survival determinants of construction consulting organization during economic contraction in Nigeria using quantity surveying firms as a focal point.

The study adopted the descriptive-survey design and quantitative data were collected through questionnaire purposely administered to quantity surveying firms in the Southwestern part of Nigeria. The data obtained from 99 quantity surveying firms on survival determinants were analysed using various statistical analysis such as mean score, standard deviation, Mann–Whitney U test, Kruskal–Wallis H test, and so on. Principal component analysis was used to identify the principal components of survival determinants, while the factors were prioritized using fuzzy synthetic evaluation (FSE).

The result of the analysis reveals eight factors that significantly determines the survival of firms during the period of economic contraction. Furthermore, the eight grouped factors were prioritized accordingly namely firm's innovation and diversification, ownership structure and networking, education level and management skills, and so on.

This study investigated the survival determinants of quantity surveying firms and prioritized it with the opinions of principal partners in quantity surveying establishments. As against obtaining large survey responses from all quantity surveyors in the study area that may not have practical experience of managing firms, the limited responses received provide valid basis to broaden the horizon of professionals and other stakeholders on the key determinants for firms to survive economic turmoil.

This study contributes to the body of knowledge by providing information on prioritized factors that must be considered in an appropriate order by quantity surveying firms to survive economic contraction.

The purpose of this article is (1) to carry out an ambivalent analysis of the determinants (benefits/risks) of the adoption of cultured meat, (2) to identify their impacts on consumers’ attitudes (cognitive, affective and conative) and (3) to propose a research agenda.

A systematic review of the relevant literature was conducted. The authors selected 86 articles that were coded using NVivo 12 software according to the theoretical framework chosen for this study: (1) consumer attitude ambivalence (benefit–risk) – conflicting presence of positive and negative attitudes in decision-making, (2) the consumer preference theory – choice of consumers based on utility maximisation or best characteristics/determinants and (3) the three-dimensional perspective of attitude – cognitive, affective and behavioural components. The authors followed the methodological steps (formulation of the research question, identification of relevant scientific studies, evaluation of the quality of studies, summary of evidence and interpretation of results) recommended by Lipsey and Wilson (2001) and Tranfield et al. (2003). Several keywords were drawn from a study by Bryant and Barnett (2019) on cultured meat (CM) nomenclature and its impact on consumer acceptance.

The identified articles were relatively recent (84/86 articles were published after 2010) and in the fields of agriculture and ethical agriculture (22/86), policy and regulations (12/86) and psychology (11/86). Content analysis helped identify four types of ambivalent determinants for the adoption of cultured meat: ethics, intrinsic, informational and belief. The results suggest the existence of a group of “dominant” determinants for each attitude component. Thus, the dominant determinants of cognitive, affective and conative components are informational, ethical and intrinsic determinants, respectively.

This research is based on a systematic review of literature and is a review of the narrative literature that provides an overview of what is known about cultured meat adoption. The main weakness of this type of method is the feasibility generally associated with the existence (and a sufficient number) of studies that can be included. Other types of the meta-analytic method could have been used and could have explored different measures and biases (e.g. effect sizes, statistical power, sampling error, measurement error and publication bias). Also, as a food technology whose social acceptability would be influenced by all stakeholders, it would be relevant to expand the analysis to other types of stakeholders.

Little is still known to the public about the adoption mechanisms of this technology. In terms of behaviour, Siegrist et al. (2018) suggest that new studies should focus on factors that influence the individual differences in the willingness of consumers to eat or purchase cultured meat. By identifying the dominant target influence of informational determinants on cognitive components, that of ethical determinants on affective components and finally that of intrinsic determinants on conative attitudes, this article offers a first avenue of solution to businesses operating in this new industry, as well as to public authorities, to improve the acceptance of cultured meat. Private businesses will benefit from the results of this research by understanding the underlying motivations of consumers to adopt this type of innovation in order to adjust future marketing.

This article, through better understanding of the psychological mechanisms that contribute to its social acceptability amongst the population, has the potential to improve educational campaigns for this technology. The results could thus guide both public policies as well as the regulation of activities related to cultured meat in the coming years, professional orders, private businesses and the general public. It thus provides initial insight needed to understand this public debate.

Research addressing cultured meat has come primarily from agribusiness and environmental and biological sciences. The authors highlighted the need for interdisciplinary collaboration between biological and social sciences to address ethical issues. This article, via multidisciplinary systematic reviews, links environmental/biological sciences and social sciences, and management.