Search results

This study aims to examine the effectiveness of an integrated intervention program for alcoholism (IIPA) for improving verbal encoding and memory, visuospatial construction, visual memory and quality of life (QoL) in persons with alcohol dependence.

The sample comprised treatment-seeking alcohol-dependent persons (n = 50), allotted into two groups: (1) the treatment as usual (TAU) group (n = 25) and (2) the treatment group (n = 25)]. The groups were matched on age (±1 year) and education (±1 year). The TAU group received standard pharmacological treatment, psychotherapeutic sessions on relapse prevention and yoga for 18 days, while the treatment group received IIPA sessions in addition to the usual treatment. Auditory verbal learning test, complex figure test and QoL scale were administered at pre- and post-treatment along with screening measures.

The two groups were comparable on demographic variables, clinical characteristics and outcome measures at baseline. Pre- to post-treatment changes (gain scores) comparison between the treatment and TAU groups revealed a significant difference in verbal encoding, verbal and visual memory, verbal recognition, visuospatial construction and QoL.

This study suggests that IIPA is effective for improving learning and memory in both modality (verbal and visual) and QoL in persons with alcoholism. The IIPA may help in better treatment recovery.

The IIPA may help in treatment for alcoholism and may enhance treatment efficacy.

IIPA is effective for improving learning and memory in both modalities and QoL in persons with alcohol dependence. The IIPA may help in better treatment recovery.

Recently, disruptive technologies (DTs) have proposed several innovative applications in managing logistics and promise to transform the entire logistics sector drastically. Often, this transformation is not successful due to the existence of adoption barriers to DTs. This study aims to identify the significant barriers that impede the successful adoption of DTs in the logistics sector and examine the interrelationships amongst them.

Initially, 12 critical barriers were identified through an extensive literature review on disruptive logistics management, and the barriers were screened to ten relevant barriers with the help of Fuzzy Delphi Method (FDM). Further, an Interpretive Structural Modelling (ISM) approach was built with the inputs from logistics experts working in the various departments of warehouses, inventory control, transportation, freight management and customer service management. ISM approach was then used to generate and examine the interrelationships amongst the critical barriers. Matrics d’Impacts Croises-Multiplication Applique a Classement (MICMAC) analysed the barriers based on the barriers' driving and dependence power.

Results from the ISM-based technique reveal that the lack of top management support (B6) was a critical barrier that can influence the adoption of DTs. Other significant barriers, such as legal and regulatory frameworks (B1), infrastructure (B3) and resistance to change (B2), were identified as the driving barriers, and industries need to pay more attention to them for the successful adoption of DTs in logistics. The MICMAC analysis shows that the legal and regulatory framework and lack of top management support have the highest driving powers. In contrast, lack of trust, reliability and privacy/security emerge as barriers with high dependence powers.

The authors' study has several implications in the light of DT substitution. First, this study successfully analyses the seven DTs using Adner and Kapoor's framework (2016a, b) and the Theory of Disruptive Innovation (Christensen, 1997; Christensen et al., 2011) based on the two parameters as follows: emergence challenge of new technology and extension opportunity of old technology. Second, this study categorises these seven DTs into four quadrants from the framework. Third, this study proposes the recommended paths that DTs might want to follow to be adopted quickly.

The authors' study has several managerial implications in light of the adoption of DTs. First, the authors' study identified no autonomous barriers to adopting DTs. Second, other barriers belonging to any lower level of the ISM model can influence the dependent barriers. Third, the linkage barriers are unstable, and any preventive action involving linkage barriers would subsequently affect linkage barriers and other barriers. Fourth, the independent barriers have high influencing powers over other barriers.

The contributions of this study are four-fold. First, the study identifies the different DTs in the logistics sector. Second, the study applies the theory of disruptive innovations and the ecosystems framework to rationalise the choice of these seven DTs. Third, the study identifies and critically assesses the barriers to the successful adoption of these DTs through a strategic evaluation procedure with the help of a framework built with inputs from logistics experts. Fourth, the study recognises DTs adoption barriers in logistics management and provides a foundation for future research to eliminate those barriers.

The purpose of this study is to construct the first short-term financial distress prediction model for the Spanish banking sector.

The concept of financial distress covers a range of different types of financial problems, in addition to bankruptcy, which is not common in the sector. The methodology used to predict financial problems was artificial neural networks using traditional financial variables according to the capital, assets, management, earnings, liquidity and sensibility system, as well as a series of macroeconomic variables, the impact of which has been proven in a number of studies.

The results obtained show that artificial neural networks are a highly suitable method for studying financial distress in Spanish credit institutions and for predicting all cases in which an entity has short-term financial problems.

This is the first work that tries to build a model of artificial neural networks to predict the financial distress in the Spanish banking system, grouping under the concept of financial distress, apart from bankruptcy, other financial problems that affect the viability of these entities.

Despite various governmental efforts, female entrepreneurship in the UAE is still not a popular option among women. The purpose of this study is to identify the enablers to female entrepreneurship and to establish relationships among them.

This research uses a two-phased approach. In the first-phase, an empirical study on female entrepreneurs was conducted to find out the most important enablers from among a set of variables identified through a comprehensive literature review. In the second-phase, using interpretive structural modeling, a hierarchy-based model is developed among the most important enablers. Further, these enablers are also classified depending on their driving power and dependence.

Survey results indicate that female entrepreneurs consider enablers as the driving force in creating an entrepreneurial culture. Further, the hierarchy-based model developed in this research helps to identify variables that are of strategic importance and require utmost attention.

The framework presented in this study can be used effectively by the policymakers to develop suitable strategies for improving entrepreneurial behavior among women in the United Arab Emirates.

The novelty of this approach is the integration of questionnaire and interpretive structural modeling methodology and classifying enablers in four clusters. The research provides useful insights about the perception of female entrepreneurs about the entrepreneurial culture in the United Arab Emirates, and a relationship model that may serve as a decision tool for improving female entrepreneurship.

This study aims to investigate the factors that influence South African customers to potentially switch from one bank to another. Instead of using established models and survey techniques, the research measured social media sentiment to measure threats to switch.

The research involved a 12-month analysis of social media sentiment, specifically customer threats to switch banks (churn). These threats were then analysed for co-occurring themes to provide data on the reasons customers were making these threats. The study used over 1.7 million social media posts and focused on all five major South African retail banks (essentially the entire sector).

This study concluded that seven factors are most significant in understanding the underlying causes of churn. These are turnaround time, accusations of unethical behaviour, billing or payments, telephonic interactions, branches or stores, fraud or scams and unresponsiveness.

This study is unique in its measurement of unsolicited social media sentiment as opposed to most churn-related research that uses survey- or customer-data-based methods. In addition, this study observed the sentiment of customers from all major retail banks across 12 months. To date, no studies on retail bank churn theory have provided such an extensive perspective. The findings contribute to Susan Keaveney’s churn theory and provide a new measurement of switching threat through social media sentiment analysis.

The coronavirus disease (COVID-19) pandemic generated a worldwide financial crisis by impacting several links of the supply chain, however companies can take advantage by quantitatively measuring the disruptive impacts.

This study sought to develop the failure mode and effect analysis and supply chain resilience (FMEA-SCR), a hybrid tool developed using a potential failure mode and effect analysis (FMEA) applied to supply chain resilience (SCR) and taking into account the capability factors and business processes.

In order to validate, the proposed model was applied into two different organizational study cases: an university and a cooperative managing urban solid wastes with recyclable potential (MSWRP). Through the procedures described here any organization can understand and assess in a simplified way the impacts over their supply chain generated by such a crisis.

This study synthesizes three different procedures into a single method called FMEA-SCR, allowing organizations to understand and assess in a simplified way, the impacts over their supply chain generated by COVID-19. To this end, it brought together the studies developed by Rajesh and Ravi (2015) and Curkovic et al. (2015), on possible causes of disruptions in SC, the capability factors of Pettit et al. (2010) used by organizations to mitigate the effects of disruptions, besides Lambert's and Croxton (2005) business processes, thus weaving a method that allows organizations to visualize, analyze and classify the pandemic impacts over their supply chain.

This paper aims to understand stakeholders' sentiments with respect to company policies in the water utilities (WU) sector and to explore if and how these sentiments could be a source for organisational learning.

This study investigates the use of social media in WUs’ and stakeholders’ reactions as a source of data for organisational learning. This paper relies on a mixed-methods approach based on sentiment analysis of Facebook (FB) pages and semi-structured interviews with sustainability managers from a sample of Italian WUs.

Findings show that WUs increasingly use FB mainly to promote and disclose environmental issues and as a source of information for organisational learning. A longitudinal analysis of environmental disclosure via FB reveals a growing trend of both companies’ posts and stakeholder interactions and significant differences among organisations in their ways of using information and knowledge obtained from social media.

Theoretically, this paper builds an original link between disclosure via social media and organisational learning processes. Empirically, to the best of the authors’ knowledge, this is one of the first studies to identify the quantity and quality of environmental disclosure via FB and the related stakeholders’ reactions.

This study presents the development of a supply chain (SC) observatory, which is a benchmarking solution to support companies within the same industry in understanding their positioning in terms of SC performance.

A case study is used to demonstrate the set-up of the observatory. Twelve experts on automatic equipment for the wrapping and packaging industry were asked to select a set of performance criteria taken from the literature and evaluate their importance for the chosen industry using multi-criteria decision-making (MCDM) techniques. To handle the high number of criteria without requiring a high amount of time-consuming effort from decision-makers (DMs), five subjective, parsimonious methods for criteria weighting are applied and compared.

A benchmarking methodology is presented and discussed, aimed at DMs in the considered industry. Ten companies were ranked with regard to SC performance. The ranking solution of the companies was on average robust since the general structure of the ranking was very similar for all five weighting methodologies, though simplified-analytic hierarchy process (AHP) was the method with the greatest ability to discriminate between the criteria of importance and was considered faster to carry out and more quickly understood by the decision-makers.

Developing an SC observatory usually requires managing a large number of alternatives and criteria. The developed methodology uses parsimonious weighting methods, providing DMs with an easy-to-use and time-saving tool. A future research step will be to complete the methodology by defining the minimum variation required for one or more criteria to reach a specific position in the ranking through the implementation of a post-fact analysis.

The German Supply Chain Due Diligence Act (GSCDDA), as a comprehensive regulation for due diligence in supply chains, will exert profound pressure on companies’ sustainable supply chain management (SSCM). This study aims to examine the affected stakeholders’ polarizing expectations stemming from the GSCDDA, the resulting impacts on SSCM and how these findings compare with theoretical SSCM developments.

From 5,490 GSCDDA posts on X (formerly “Twitter”), the authors extracted 556 qualitative posts illustrating the GSCDDA discourse and analyzed them from a stakeholder perspective. The posts were classified according to the dimensions of stakeholder groups and expectations (i.e. challenges and opportunities). The authors then synthesized the posts across these dimensions and compared the identified expectations with the SSCM literature.

Seven stakeholder groups were identified, along with nine challenges (e.g. legal flaws) and four opportunities (e.g. increased transparency). The synthesis of both components revealed highly discussed and conflicting expectations. The theoretical SSCM developments partly differ from the discourse, indicating discernible gaps between theory and practice

Identifying key stakeholder groups supports building synergies between GSCDDA implementers and stakeholders to tackle their challenges and reinforce opportunities.

Due to the growing prevalence of supply chain due diligence regulations, it is essential to consider the legal implications for SSCM. This study explores the link between due diligence concepts and SSCM, and to the best of the authors’ knowledge, this is the first study to analyze how legal pressure shapes stakeholders’ expectations on companies’ SSCM.

This study aims to discuss what prompted this organization to embark on the journey of transformational change, challenges faced strategies adopted to overcome challenges, leadership role and outcomes.

The descriptive approach is used to comprehend the transformational change process in this gigantic public sector undertaking (PSU). To have an idea of the effectiveness of the change process, the pre- and post-change performance of the company was taken into account through collection and analysis of physical and financial parameters. However, focus of this paper is concentrated on the transformation process and its chronological sequence only. Human resource productivity trend and organization development interventions adopted over the years were also observed along with conducting a sentiment analysis of the employees who lived through this entire change process in the organization.

The case study describes how this Indian PSU went through the process of transformational change management and leaves the reader to assess the degree and extent of success of the approach and strategy of the company in this regard. There may be many what-if situations and contingencies in this case for readers to explore for suggestions and solutions and finding new possibilities.

Change management is not a new exercise for the Indian corporate sector. What makes this case unique is the pro-active action initiated by a traditional high-performing and well-protected PSU to anticipate the future challenges and initiate action to overcome these. Change agents must “rewire” the plane while it is flying if the organization hopes to survive and perhaps prosper in the future. This case study is a first-hand account of the change process happening in a gigantic Indian PSU with Maharatna status.