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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.

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.

This paper examines rent determinants and their relationship with commercial office property rents.

The method adopted in this study differs from that of previous studies on this topic. Firstly, based on the survey of the viewpoints of experts, Relative Importance Index (RII) analysis was used to identify rent determinants and to rank and ensure their relevance and validity in the Sri Lankan context. Secondly, sampling of data related to 115 office properties collected from property tenants and landlords located within the central built-up area of Colombo City was conducted using a multi-methods approach to carry out an objective hedonic analysis of office rents.

This research utilizes RII and hedonic models to provide insights into determinants and relationships. Both analyses confirm that the three top drivers of commercial office rent are distance from the major town center, availability of parking space and the condition of the property. In addition to these three factors, hedonic models reveal that the age of the property and the availability of a conference hall also play a relevant role in explaining office rents. Given the disparities in the findings of the two methods, further examination was able to confirm that factors such as distance from the major town center, parking availability, age of the property, presence of a conference hall, building condition, floor size, business type and type of building are likely to influence commercial office rent. These findings reflect elements such as the quality, newness and better facilities of different office properties.

This systematic study and analysis of office rent for the guidance of real estate investors can support sound investment decisions, potentially leading to more financially sound property development, reduced public debt levels and improved public-private financing. Further, the research findings offer valuable insights to real estate investors, developers and planners regarding location decisions for office development quality enhancements in future office developments.

This research provides fresh insights into the local scale office market, an area where limited evidence currently exists. Further, the methodology adopted provides evidence that hedonic analysis, supported by a multi-method approach, can mitigate the subjective judgments made by professionals.

The purpose of this paper is to explore the determinants of three different types of bank liquidity: funding liquidity, liquidity creation, and stock liquidity in emerging markets.

It uses an extensive set of data from all the listed banks of Brazil, Russia, India, China, and South Africa, collectively known as the BRICS countries, spanning the period 2002-2014. Multiple linear regression has been used to estimate the coefficients of the determinants.

In case of emerging markets, bank size is not a determinant of different types of liquidity, except funding liquidity. Besides, the recent financial crisis had an impact on funding liquidity as well as “cat nonfat” measure of liquidity creation but it did not affect “cat fat” measure and stock liquidity. The variation in funding liquidity is also explained by the profitability and the riskiness of the bank. Effective interest rate, national savings rate, and inflation rate are also the determinants of funding liquidity. Bank-specific determinants of liquidity creation include bank leverage and profitability, and macroeconomic determinants include stock market index, effective interest rate, and unemployment rate. The variation in stock liquidity of the bank is explained by profitability and price of stocks, trading volume, volatility of stock returns, and percentage change in real gross domestic product. Neither market capitalization nor stock market index is the determinant of stock liquidity of the banks.

This study uses the data from publically listed banks only.

The findings of this study may be used by the policy makers and bank managers in the emerging markets to design better policies and to strengthen the banking system to avoid financial turmoil in future.

Most of the existing studies focus on bank liquidity in developed countries and studies aiming on emerging countries are rare. The existing studies focus more on funding liquidity and liquidity creation but to the best of the authors’ knowledge, none of the studies analyze the determinants of banks’ stock liquidity. So, this study bridges the above mentioned gaps by focusing on bank liquidity in emerging markets, and exploring the determinants of the stock liquidity of the banks.

The purpose of this paper is to provide a portrait of the main managerial and organizational determinants of organizational capability to innovate (OCI). Despite its importance, research on the subject seems limited, and little attempt has been made, over the years, to offer an in-depth and simultaneous analysis of these particular determinants, as well as an exploration of the underlying and complex mechanisms explaining their relationships to OCI.

A systematic review of articles published between 1991 and 2018 was conducted in ProQuest (ABI/INFORM Collection) and Scopus databases. A total of 64 articles were selected and analysed through the use of a coding grid.

Results highlight five key OCI determinants, namely: leadership, support, communication, culture, and learning. By using the dynamic capabilities theory (DCT) as a framework, this research suggests ways to better understand the dynamic action of these determinants as well as their contributions to OCI. Findings also suggest that OCI should be defined at the confluence of three perspectives (human, procedural and environmental aspects) to embrace the multiple facets of this complex construct. Proposals for future research are provided on how OCI can be better examined.

This research helps to understand the five core determinants through an integrated and holistic view and represents the first attempt to systematically analyse the scientific literature on OCI through the DCT lens.

The purpose of this paper is to explore how different determinants impact specific information quality (IQ) dimensions of shared demand-related information in dyadic supply chain relationships.

Through a qualitative case study of three manufacturer–supplier dyads in the European automotive industry, a range of methods are used to collect data about 168 possible IQ deficiency situations. IQ deficiencies are identified in 50 situations and determinants thereof are explored.

Findings show how inter-organisational collaboration, intra-organisational process support and composite information sharing directly impact five pragmatic IQ dimensions (relevance, accessibility, credibility, understandability and ease of operation) – at times beneficially, detrimentally, varyingly and conflictingly. Furthermore, the findings show how the determinant impact on ease of use-related IQ dimensions is moderated by information sharing facets.

The paper extends previous research by showing how information sharing acts as both a determinant and moderator of pragmatic IQ. It furthermore details previous research by showing how previously examined determinants of IQ impact specific IQ dimensions.

The generated propositions of how determinants impact pragmatic IQ can guide managers to identify key drivers of successful information sharing.

Since IQ mediates the linkage between information sharing and performance, this research helps explaining conflicting results regarding the value of information sharing. It also guides several strands of future research, such as hypothesis testing and exploratory and conceptualising studies.

The purpose of this paper is to test a model of banking system trust as an antecedent of bank trust and bank loyalty. Six determinants of trust and loyalty are included: competence, stability, integrity, customer orientation, transparency, and value congruence. The study provides insights which determinants are crucial for explaining bank trust and bank loyalty, and thus for rebuilding trust and loyalty.

Survey among 1,079 respondents of 18 years and older in The Netherlands on person trust, system trust, bank trust, and their scores on determinants of trust and loyalty. Structural equations modeling (AMOS) has been performed to provide insights into the relationships between concepts such as person trust, system trust, bank trust, and bank loyalty. The importance of determinants to explain bank trust and bank loyalty has been assessed as well.

Integrity is the most important determinant of bank trust. Transparency, customer orientation, and competence are also significant. Trust is a strong predictor of loyalty. Determinants explaining bank loyalty are: competence, stability, transparency, and value congruence. System trust is also a determinant of bank trust. The meaning of these results is discussed in the paper, as well as the managerial implications of these findings.

Data were collected in May 2014 with a large sample, when the financial crisis came to an end. Distrust still remained as a consequence of the crisis. Banks are now rebuilding trust and loyalty. This research provides indications which determinants of trust and loyalty are important in this process and should be focused upon. A longitudinal study how trust and loyalty are developing would give insights and feedback on managerial actions.

Results provide insights into the causes and reasons of (dis)trust. From this study, banks get insights with a priority matrix which determinants are below par but important for specific banks and should be focused on and improved at the short term.

Trust in banks and other financial institutions is crucial for the functioning of the banking system and for society at large. Restoring trust is a matter of fundamental changes of the bank-customer relationships, not only by communication but by sincere behavior (integrity) and benevolence in the customer interest.

The authors are not aware of research using all six determinants (competence, stability, integrity, customer orientation, transparency, and value congruence) to explain and predict bank trust and bank loyalty, and their implications for trust and loyalty in banks.

Social determinants of stressful events (SE) play an important role in justifying the cause of inequality in the experience of SE. The purpose of this study is to investigate the determinants that impact on inequality in the experience of SE.

The statistical population of this study includes all residents of Tehran. The statistical sample was 5,895 people who were selected by multistage cluster method and were proportional to the population size. The research tool is a researcher-made questionnaire designed to measure SE in Tehran, which includes 11 psychological stressors. The Oaxaca–Blinder decomposing method was used to analyze data.

In a total of 11 psychological SE, in 6 of those events, there was significant inequality in the experience of SE. Concentration Index (CI) of political SE is (CI = −0.27, 95% CI: −0.47, −0.07) and in favor of the rich (pro-rich). Education (OR = 1.60) in poor group and region development in poor and rich (respectively in all of the following) (OR = 0.42–0.73) are the main determinants of inequality in this stressor. CI of neighborhood underdevelopment SE is (CI = −0.47, 95% CI: 0.66, −0.28) and pro-rich. Education (OR = 1.26–1.27) and region development (OR = 1.18–2.24) are the main determinants of inequality in this stressor. CI of livelihood problems SE is (CI = −0.58, 95% CI: 0.68, −0.32) and pro-rich. Education (OR = 1.40) and health status (OR = 1.63) in poor group are the main determinants of inequality in this stressor. CI of future uncertainty SE is (CI = −0.12, 95% CI: 0.34, −0.08) and pro-rich. Gender (OR = 1.22) in poor group and region development (OR = 0.24–0.58) are the main determinants of inequality in this stressor. CI of education problems (CI = 0.19, 95% CI: 0.05, 0.32) and pro-poor. Age (OR = 0.32–0.34) and education (OR = 3.65–3.30) are the main determinants of inequality in this stressor. CI of housing problems is (CI = −0.29, 95% CI: −0.49, −0.08) and pro-rich. Education (OR = 1.31) and region development (OR = 1.64) in poor group are the main determinants of inequality in this stressor.

The first limitation is related to the level of data analysis, and the second limitation is the lack of comprehensive data on social determinants.

Social determinants affecting the formation of inequality in the experience of SE. Some social determinants, such as the level of education and development of the region, play a more prominent role in justifying inequality in the experience of stress between rich and poor groups.

Inequality in the experience of SE is a serious threat to mental and social health. One of the ways to reduce the experience of psychological and social stress is to pay attention to social determinants that play a role in the formation of stress.

This original paper was conducted by examining the effect of social determinants on the formation of inequality in the experience of stress, which draws the serious attention of policymakers.

Presents details of a study identifying the performance determinants required of chief executive officers (CEOs) and senior managers. The study compares current findings in management competences (referred to here as performance determinants) with previous research in this field. Although previous research has identified such performance determinants, the bulk of the literature has focused on middle management rather than on senior management. Sixty‐six CEOs and senior managers in the public sector were interviewed. Preliminary analysis of the data indicated that there was little evidence of a generic model identifying the performance determinants for senior managers.

An attempt is made in this paper to discriminate among four groups of transfer pricing methods namely: market price, cost, negotiation, and other methods, according to the transfer pricing objectives and other environmental issues (i.e. transfer pricing determinants). Discrimination is attempted on the data collected in the study of UK companies described in the earlier paper “A Survey of UK Transfer Pricing Practice — Some Preliminary Findings”. The aim of the discrimination is to evaluate the relationship between the transfer pricing method and transfer pricing determinants. This evaluation enables the prediction of transfer pricing method for new cases according to the company's perception of the relative importance of the transfer pricing determinants.