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This study aims to identify the determining factors of perceived altruism and attitude toward an inclusive sponsorship activation, as well as the impact of these variables on the attitude toward the sponsor.

Online survey data were obtained from 1,228 respondents from France, the UK and South Africa. The data were analyzed using partial least squares structural equation modeling (PLS-SEM).

The results show that the cause-brand fit has a strong positive impact on the perceived altruism toward the motivations underlying inclusive activation, while skepticism toward advertising has a very weak negative impact. In return, perceived altruism positively influences the attitude toward inclusive activation and sponsor attitude. Furthermore, this attitude toward inclusive activation is positively influenced by involvement in women’s soccer and France men’s national football team identification. The attitude toward inclusive activation also positively influences the attitude toward sponsor attitude. However, contrary to what had been advanced, identification with the France women’s national football team and the nationality of the respondents (French, British or South African) had no impact on the attitude toward inclusive activation, while the perceived importance of the cause had very weak impact on attitudes toward inclusive activation.

This study highlights the potential benefits of investing in inclusive sponsorship activations, particularly with respect to their positive impact on consumer attitude toward sponsor attitude. It also highlights the importance of establishing, in advance, a strong association between the brand image and the cause supported, so that the motivations underlying the inclusive activations are perceived as more altruistic.

There is extensive literature on the determinants of job tenure insecurity. However, very little is known about the individual drivers of labour market insecurity. Additionally, while a piece of literature shows that volunteering improves workers' income, no study considers volunteering as an activity which could help workers to feel more confident about their perception of labour market insecurity if they lost or resigned their jobs. Therefore, purpose of this paper is to study whether workers who volunteer are less likely to perceive labour market insecurity.

The paper employs data from the sixth European working conditions survey which provides a great deal of information on working conditions. For the empirical investigation, probit model as well as robustness analysis have been implemented.

Results show that employees who do voluntary activities have a greater likelihood of declaring perceived labour market insecurity, which is nearly 3 percentage points lower, than employees who do not volunteer. Findings suggest that governments need to improve the relationship between for-profit and non-profit sectors to encourage volunteering.

This is the first study which considers volunteering as an activity which could help workers to feel more confident about their perception of “labour market insecurity”. Most of the studies on “labour market insecurity” do not focus on the workers individual characteristics but mainly on the labour markets institutional characteristics and welfare regimes differences.

The study aims to discern the primary obstacles confronted by the implementing agencies in their efforts to foster financial inclusion through the “Pradhan Mantri MUDRA Yojana” (PMMY).

To collect primary data, a semi-structured questionnaire was developed. Around 120 loan officers from the implementing agencies (Scheduled Commercial Banks (SCBs), Regional Rural Banks (RRBs), Small Finance Banks (SFBs), Non-Banking Financial Companies (NBFCs) and Micro- Finance Institutions (MFIs)) of Haryana were randomly selected to fulfill the objectives. To categorize the perceived problems into discrete factors, the “factor analysis” technique was employed. The scales were then regressed on factors linked to the demographic characteristics of the loan officers to validate the hypotheses.

The study highlighted the primary obstacles impeding the advancement of financial inclusion, which encompass a range of factors. These include challenges in management, infrastructure, politics, finance and technology. Furthermore, the study established the association of the explanatory variables, namely gender, age, educational qualification, location and experience of the officers, with the extracted constraints. Notably, the experience of loan officers emerged as the most influential variable contributing to the promotion of financial inclusion through the scheme.

The current body of literature lacks any empirical investigation focusing on the perspectives of the implementing agencies regarding the challenges they encounter in advancing FI. Given the significance of FI in India, where access to formal financial services remains a critical issue, this research adds value by addressing the gaps in understanding the problems encountered.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-06-2023-0462

In the era of artificial intelligence (AI), algorithms have gained unprecedented importance. Scientific studies have shown that algorithms are frequently mentioned in papers, making mention frequency a classical indicator of their popularity and influence. However, contemporary methods for evaluating influence tend to focus solely on individual algorithms, disregarding the collective impact resulting from the interconnectedness of these algorithms, which can provide a new way to reveal their roles and importance within algorithm clusters. This paper aims to build the co-occurrence network of algorithms in the natural language processing field based on the full-text content of academic papers and analyze the academic influence of algorithms in the group based on the features of the network.

We use deep learning models to extract algorithm entities from articles and construct the whole, cumulative and annual co-occurrence networks. We first analyze the characteristics of algorithm networks and then use various centrality metrics to obtain the score and ranking of group influence for each algorithm in the whole domain and each year. Finally, we analyze the influence evolution of different representative algorithms.

The results indicate that algorithm networks also have the characteristics of complex networks, with tight connections between nodes developing over approximately four decades. For different algorithms, algorithms that are classic, high-performing and appear at the junctions of different eras can possess high popularity, control, central position and balanced influence in the network. As an algorithm gradually diminishes its sway within the group, it typically loses its core position first, followed by a dwindling association with other algorithms.

To the best of the authors’ knowledge, this paper is the first large-scale analysis of algorithm networks. The extensive temporal coverage, spanning over four decades of academic publications, ensures the depth and integrity of the network. Our results serve as a cornerstone for constructing multifaceted networks interlinking algorithms, scholars and tasks, facilitating future exploration of their scientific roles and semantic relations.

This study aims to explore how the shift from traditional to digital banking transforms the nature of trust between banks and their younger clients (aged 18–35) from the perspective of bank employees.

Qualitative semi-structured interviews with representatives of Ukrainian classical banks and neobanks were conducted. The interviews were analysed using the theoretical approach of institution-based and social network-based trust to identify the key distinctions between the nature of trust in traditional and digital banking.

The employees of the banks reported that digitalization processes have helped to mitigate trust issues; as a result, their banks have not experienced any difficulties in this regard among young people. Furthermore, social networks, particularly social approval, were found to be significant factors for establishing trust in digital banking among young people.

The results of this study could assist bank managers in adapting their strategies for cultivating trust among younger clients and aiding international law regulators and government institutions in preventing unintended circumstances in financial services. These contributions were shaped by the study’s limitations, including its focus on only two concepts of trust building: institution-based and social network-based, as well as its specific Ukrainian context.

This study highlights social approval as a valuable constituent of the trust-building process that influences trust in institutions. Furthermore, while gaining social approval – particularly through digital platforms – can promote trust-building among young people, this “easy way” may have negative societal consequences by endorsing unscrupulous institutions.

In this study, the authors seek to understand factors that naturally influence users to adopt two-factor authentication (2FA) without even trying to intervene by investigating factors within individuals that may influence their decision to adopt 2FA by themselves.

A total of 1,852 individuals from all 34 provinces in Indonesia participated in this study by filling out online questionnaires. The authors discussed the results from statistical analysis further through the lens of the loss aversion theory.

The authors found that loss aversion, represented by higher income that translates to greater potential pain caused by losing things to be the most significant demographic factor behind 2FA adoption. On the contrary, those with a low-income background, even if they have some college degree, are more likely to skip 2FA despite their awareness of this technology. The authors also found that the older generation, particularly females, to be among the most vulnerable groups when it comes to authentication-based cyber threats as they are much less likely to adopt 2FA, or even to be aware of its existence in the first place.

Authentication is one of the most important topics in cybersecurity that is related to human-computer interaction. While 2FA increases the security level of authentication methods, it also requires extra efforts that can translate to some level of inconvenience on the user's end. By identifying the associated factors from the user's ends, a necessary intervention can be made so that more users are willing to jump on the 2FA adopters' train.