Search results

This paper presents an interactive fuzzy satisfying method by assuming that the decision maker (DM) has fuzzy goals for each of the objective functions in multiobjective nonlinear programming problems. The fuzzy goals of the DM are quantified by eliciting the corresponding membership functions through the interaction with the DM. After determining the membership functions for each of the objective functions, in order to generate a candidate for the satisficing solution which is also a Pareto optimal, the DM selects an appropriate standing membership function and specifies his/her aspiration levels of achievement of the other membership functions, called constraint membership values. For the DM's constraint membership values, the corresponding constraint problem is solved and the DM is supplied with the Pareto optima] solution together with the trade‐off rates between a standing membership function and each of the other membership functions. Then by considering the current values of the membership functions as well as the trade‐off rates, the DM acts on this solution by updating his/her constraint membership values. In this way, the satisficing solution for the DM can be derived efficiently from among a Pareto optimal solution set by updating his/her constraint membership values. On the basis of the proposed method, a time‐sharing computer program is written and an application to regional planning is demonstrated along with the corresponding computer outputs.

This study aims to identify and assess the key ethical challenges associated with integrating artificial intelligence (AI) in knowledge-sharing (KS) practices and their implications for decision-making (DM) processes within organisations.

The study employs a mixed-methods approach, beginning with a comprehensive literature review to extract background information on AI and KS and to identify potential ethical challenges. Subsequently, a confirmatory factor analysis (CFA) is conducted using data collected from individuals employed in business settings to validate the challenges identified in the literature and assess their impact on DM processes.

The findings reveal that challenges related to privacy and data protection, bias and fairness and transparency and explainability are particularly significant in DM. Moreover, challenges related to accountability and responsibility and the impact of AI on employment also show relatively high coefficients, highlighting their importance in the DM process. In contrast, challenges such as intellectual property and ownership, algorithmic manipulation and global governance and regulation are found to be less central to the DM process.

This research contributes to the ongoing discourse on the ethical challenges of AI in knowledge management (KM) and DM within organisations. By providing insights and recommendations for researchers, managers and policymakers, the study emphasises the need for a holistic and collaborative approach to harness the benefits of AI technologies whilst mitigating their associated risks.

Identification of dominant approaches and applied practices in the field of diversity and diversity management (DM) in Polish companies in the context of trends on labor market. Although there is not much diversity in Poland now, it is expected that there will be more age related and ethnic diversity in future.

Semi-structured interviews with HR specialist in 50 innovative companies (medium and large companies) were conducted. A synthesis of the current achievements of Polish research in this area was also carried out.

The concept of DM is not popular yet in Polish organizations. There are mostly observed declarative activities concentrating on image-related benefits and focusing on the equal employment opportunity. Findings are consistent with the results of other authors.

The study was limited by research methodology which presented one-sided, HR managers, view of the problem. Further studies examining other perspectives are required.

Observed trends on labor market require changes in attitudes toward diversity on organizations. A major challenge is to overcome the traditional approach. Potential benefits and threats ought to be documented, legal regulations adjusted to changes on labor market developed. The regulations ought to take the growing number of immigrants and problems associated with retirement age being lowered into consideration. Further studies are required.

The assessment of the state of DM implementation in Polish organizations in the context of labor market changes and associated challenges constitutes an original character of the present study.

As South Africa (SA) increasingly becomes overwhelmed by natural disasters, understanding disaster risk reduction (DRR) policies, institutions, processes and practices and their effects on disaster risk management (DRM) are incumbent The study reviews and empirically analyses policies, institutional frameworks and processes for disaster management in SA. Content analysis is applied to review topical secondary data, while a structured questionnaire informed by the Sendai Framework for Disaster Risk Reduction is used to collect quantitative data from a random sample of 228 disaster policy actors from five disaster-stricken metropolitan cities in five provinces in SA, namely North-West, Free State, KwaZulu-Natal, Limpopo and Mpumalanga. Empirical data were analysed using the Statistical Package for the Social Sciences (SPSS) software. Research findings reveal that SA is endowed with rich institutional policy and legal frameworks for DRM, based on the concepts of decentralisation and stakeholder participation. A positive and strong correlation between institutional framework, disaster risk identification and prioritisation, knowledge creation and management (KCM) as well as the disaster governance and DRM in SA (p = 0.000). Although the coefficient of KCM is not statistically significant, DRM behaviour was influenced at 87.2% by all four variables. Based on the recent disaster experiences and the above results, we advocate for DRR to be continuously prioritised at national and decentralised levels, to enhance effective preparedness, mitigation, disaster response and resilience building practices in SA.

Contemporary organisations are data-driven with sophisticated and strong Information Technology (IT) supporting the Business Intelligence (BI) systems. Due to the Industrial Revolution 4.0, businesses are subjected to volatility, uncertainty, complexity, and ambiguity (VUCA). The accuracy and agility of decision making (DM) play a key role in the success of contemporary organisations. Traditional methods of DM, i.e. based on tacit knowledge, are no longer relevant in the constantly altering business scenarios. Innovations in the IT domain have accomplished systems to gather and process business data at an exponential speed. Context-driven analytics along with computation capability and performance-driven visualisation have become an implicit need for businesses. BI systems offer the capabilities of data-driven DM simultaneously allowing organisations to predict the future business scenarios. Qualitative research is conducted in this chapter. In the research, interviews, questionnaires, and secondary data from previous research are used as data source. Case studies are discussed to clarify the business use cases of BI systems and their impact on managerial DM. Theoretical foundations are stated basis a thorough literature review of the available body of knowledge. The current environment demands data-driven DM in an organisation at all levels, i.e. strategic, tactical, and operational. Heterogeneous data sources add unlimited value to the decision support systems (DSSs). The BI systems have become an integral part of the technology landscape and an essential element in managerial DM. Contemporary businesses have deployed BI systems in all the functions.

Emerging market MNEs often seek to advance their domestic competitive advantage through a springboard FDI strategy, which typically takes the form of an acquisition into a developed market (DM) for knowledge resources. We argue that if this strategy is effective and beneficial, then an emerging market parent firm would seek for higher ownership and control in its later domestic acquisitions. Such benefits would be higher if there are richer knowledge resources in a DM subsidiary or in a DM local network. Such benefits would also increase over time because of the accumulation of new knowledge back home. Using a sample of 1,303 complete domestic acquisitions made by 713 Turkish firms over the period of 1987–2013, including 196 deals involving a springboard FDI strategy, we have found highly supportive empirical evidence. It is found that holding a DM subsidiary by a Turkish parent firm is associated with 33.047% higher ownership in a later domestic acquisition. Both research and practical implications are discussed.

We study a microfounded search model of exchange in the laboratory. Using a within-subjects design, we consider exchange behavior with and without an intrinsically worthless token object. While these tokens have no redemption value, like fiat money they may foster greater exchange and welfare via the coordinating role of having prices of goods in terms of tokens. We find that welfare is indeed improved by the presence of tokens provided that the economy starts out with a supply of such tokens. In economies that operate for some time without tokens, the later surprise introduction of tokens does not serve to improve welfare. We also explore the impact of announced changes in the economy-wide stock of tokens (fiat money) on prices. Consistent with the quantity theory of money, we find that increases in the stock of money (tokens) have no real effects and mainly result in proportionate changes to prices. However, the same finding does not hold for decreases in the stock of money.

Kenya is vulnerable to multiple natural hazards that lead to disasters resulting in human, economic, environmental and other losses. The promulgation and ratification of several disaster management (DM) policies, acts, conventions and the establishment of the National Disaster Management Policy Framework has placed Kenya at the international forefront. We critically analyse various Kenyan policy institutions and processes for disaster risk management (DRM), applying a mixed-methods approach. Content analysis was applied to qualitatively analyse Kenya’s DM policy and legislation documents, using Nvivo 11 Pro. Descriptive and econometric analyses were performed on empirical data from DRM key informants in Kenya using SPSS version 25.0. Only 11% of interviewees were aware of the National Disaster Policy Framework; 50% had read up to two national DM-related documents. National institutions exert highest influence in the policy formulation (78%), compared to local and international institutions (67% and 56%, respectively). Participation of local and national institutions in national DRM policy formulation was high (mean scores of 2.44/4 and 1.67/4, respectively). A weak correlation was observed between years of experience (r = 0.115, p = 0.768), and a positive but insignificant one between experience and participation in DRM policy formulation. Based on the aforementioned, we suggest that Kenya’s disaster risk reduction (DRR) implementation benefits from the high human capacity and high level of participation. However, the performance of frontline staff needs to be improved, especially regarding their knowledge of existing national DRM frameworks.

Since the 1980's, diversity management (DM) has been regarded as a relevant scholarly and practical endeavour laden with different and often contrasting rationales and conceptualisations. In this regard, the current literature on DM largely differentiates between two overarching approaches – the instrumental and the critical approach with varying conceptualisations and underlying understandings of DM. The purpose of this paper is to discuss how a paradox lens can be utilised to bridge existing understandings of diversity management.

The authors aim to discuss the current state of DM literature and reconceptualise DM from a paradox lens.

The authors argue that the use of a paradox lens on DM allows for challenges to be brought forward instead of ignored or hidden away by illuminating and actively acknowledging both the liberating but also the challenging and oftentimes constraining experiences for the actors involved. Thus, a Paradox lens offers space for embracing and utilising paradoxes when working with diversity.

Diversity management is no new concept in the field of human resource management and several scholars argue that the longstanding divide between the instrumental and critical approach remains problematic and limiting for the practice of DM. Hence, the value of reconceptualising DM from a paradox lens lies in bridging the two approaches in order to give way to viewing DM as a nuanced, dynamic and multifaceted practice that can accommodate complexity and contradictions in new and potentially beneficial manners.

This study aims to provide insights into US and Australian analysts' views regarding the relative importance of disclosing the direct method (DM) or indirect method (IM) statement of cash flows and forecasting firm performance.

Evidence is collected from responses to 104 surveys and 52 interviews completed by US and Australian analysts from 2017 to 2022. The survey and interview questions are developed with reference to the literature.

US and Australian analysts believe that the DM format provides incremental benefits compared to the IM for (1) confirming the reliability of earnings; (2) improving earnings confidence; (3) more accurate ex ante forecasts of operating cash flow and earnings; and (4) identifying opportunistic accruals manipulation. Analysts view that DM disclosure can lower firm-level cost of equity, although US interviewees more uniformly expect lower costs of equity under DM disclosure when firms yield low earnings quality. DM disclosure is also more important during unstable economic periods, as proxied by COVID-19.

Limited research currently exists regarding disclosure of the DM or IM and its impact on analysts' forecasting accuracy, earnings quality, economic uncertainty and cost of equity. Previous research has relied on archival research to examine differences between the DM and IM methods and are limited by data availability. Our findings are particularly relevant to the US market with few US firms reporting the DM format.