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This study aims to estimate the quality-adjusted changes in residential mobile consumer prices by controlling for the changes in the relevant service characteristics and quality, in a case study on Hungary between 2015 and 2021; compare the results with changes measured by the traditionally calculated official telecommunications price index of the Statistical Office; and discuss separating the hedonic price changes from the effect of a specific government intervention that occurred in Hungary, namely, the significant reduction in the value added tax rate (VAT) levied on internet services.

Since the price of commercial mobile offers does not directly reflect the continuous improvements in service characteristics and functionalities over time, the price changes need to be adjusted for changes in quality. The authors use hedonic regression analysis to address this issue.

The results show significant hedonic price changes over the observed seven-year period of over 30%, which turns out to be primarily driven by the significant developments in the comprising service characteristics and not the VAT policy change.

This paper contributes to the literature on hedonic price analyses on complex telecommunications service plans and enhances this methodology by using weights and analysing the content-related features of the mobile packages.

The purpose of this paper is to critically examine the multinational oil companies’ (MOCs) corporate social responsibility (CSR) initiatives in Nigeria. Its special focus is to investigate the impact of the global memorandum of understanding (GMoU) on mainstreaming gender sensitivity in cash crop market supply chains in the Niger Delta region of Nigeria.

This paper adopts an explanatory research design with a mixed method to answer the research questions and test the hypotheses. A total of 1,200 rural women respondents were sampled across the Niger Delta region.

Results from the use of a combined logit model and propensity score matching indicate a significant relationship between the GMoU model and mainstreaming gender sensitivity in cash crop market supply chains in the Niger Delta.

This study implies that MOCs’ CSR interventions that improve women’s access to land and encourage better integration of food markets through improved roads and increased mobile networks would enable women to engage in cash crop production.

This implies that improving access to credit through GMoU cluster farming targeted at female farmers would improve access to finance and extension services for women in cash crop production in the Niger Delta.

This research contributes to the gender debate in the agricultural value chain from a CSR perspective in developing countries and is rational for demands for social projects by host communities. It concludes that businesses have an obligation to help solve problems of public concern.

In this article, the aim is to document the divergences/convergences between the market perceptions of quality and the financial estimations for office buildings relative to the notion of centrality and the distance to the central business district (CBD).

Based on a hierarchical approach that decomposes and estimates the perceived quality of buildings from the stakeholders’ perspectives, we study the geographies of perceived quality measures in the Greater Paris Metropolis and compare them to the financial geography.

The perceived location quality decreases with distance from the CBD whereas judgments on the built structure and the workplace do not, exhibiting a ring-shaped pattern. The gradient of the components of the perceived quality are heterogeneous, having positive, negative or null values. Appraisers tend only to consider the quality of location in their estimations.

This article raises the issue of fair spatial judgments by appraisers and the financial market. Monocentricity is not the rule in the market perceptions of quality. It suggests that financial estimates are strongly biased, with mental representation of centrality as a judgmental heuristic.

With big data (BD), traditional supply chain is shifting to digital supply chain. This study aims to address the issues and challenges in the way toward the implementation of big data analytics (BDA) in sustainable supply chain management (SSCM).

The factors that affect the implementation of BDA in SSCM are identified through a widespread literature review. The PESTEL framework is used for this purpose as it covers all the political, economic, social, technological, environmental and legal factors. These factors are then finalized by means of experts' opinion and analyzed using structural equation modeling (SEM).

A total of 10 factors are finalized with 31 sub-factors, of which sustainable performance, competitive advantage, stakeholders' involvement and capabilities, lean and green practices and improvement in environmental performance are found to be the critical factors for the implementation of BDA in SSCM.

This research has taken up the case of Indian manufacturing industry. It can be diversified to other geographical areas and industry sectors. Further, the quantitative analysis may be undertaken with structured or semi-structured interviews for validation of the proposed model.

This research provides an insight to managers regarding the implementation of BDA in SSCM by identifying and examining the influencing factors. The results may be useful for managers for the implementation of BDA and budget allocation for BDA project.

The result includes green practices and environmental performance as critical factors for the implementation of BDA in SSCM. Thus the research establishes a positive relationship between BDA and sustainable manufacturing that ultimately benefits the environment and society.

This research addresses the challenges in the implementation of BDA in SSCM in Indian manufacturing sector, where such application is at its nascent stage. The use of PESTEL framework for identifying and categorizing the factors makes the study more worthwhile, as it covers full spectrum of the various factors that affect the strategic business decisions.

To elaborate the nature of fact-checking in the domain of political information by examining how fact-checkers assess the validity of claims concerning the Russo-Ukrainian conflict and how they support their assessments by drawing on evidence acquired from diverse sources of information.

Descriptive quantitative and qualitative content analysis of 128 reports written by the fact-checkers of Snopes – an established fact-checking organisation – during the period of 24 February 2022 – 28 June, 2023. For the analysis, nine evaluation grounds were identified, most of them inductively from the empirical material. It was examined how the fact-checkers employed such grounds while assessing the validity of claims and how the assessments were bolstered by evidence acquired from information sources such as newspapers.

Of the 128 reports, the share of assessments indicative of the invalidity of the claims was 54.7%, while the share of positive ratings was 26.7%. The share of mixed assessments was 15.6%. In the fact-checking, two evaluation grounds, that is, the correctness of information and verifiability of an event presented in a claim formed the basis for the assessment. Depending on the topic of the claim, grounds such as temporal and spatial compatibility, as well as comparison by similarity and difference occupied a central role. Most popular sources of information offering evidence for the assessments include statements of government representatives, videos and photographs shared in social media, newspapers and television programmes.

As the study concentrated on fact-checking dealing with political information about a specific issue, the findings cannot be extended to concern the fact-checking practices in other contexts.

The study is among the first to characterise how fact-checkers employ evaluation grounds of diverse kind while assessing the validity of political information.

This study aims to investigate how social entrepreneurial role models influence social entrepreneurial self-efficacy, social entrepreneurial intent and social entrepreneurial action, with moral obligation as a moderator.

A cross-sectional survey of 261 pupils in the South African province of the Eastern Cape was used in the research study. Structural equation modeling was used to test hypotheses.

The research revealed that having social entrepreneurial role models has a positive impact on both social entrepreneurial self-efficacy and social entrepreneurial intent. In addition, a connection was found between social entrepreneurial intent and entrepreneurial action. The influence of moral obligation was found to be a positive and a significant moderator. Moreover, the association between social entrepreneurial role models and social entrepreneurial intent was mediated by social entrepreneurial self-efficacy.

The findings are not generalizable to nonstudent samples because students constituted the sample for gathering data. Future study therefore requires considering nonstudents to generalize the outcomes. This research should be replicated in other South African provinces and other developing countries for comparative outcomes.

Since social entrepreneurial role models have been practically linked to social entrepreneurship intent and entrepreneurial efficacy, understanding the factors that influence student’s decision to start a social enterprise is critical in South Africa to develop targeted interventions aimed at encouraging young people to start new businesses. Policymakers, society and entrepreneurial education will all benefit from the findings.

This study contributes to bridging the knowledge gap as it investigates how social entrepreneurial role models influence social entrepreneurial self-efficacy, social entrepreneurial intent and social entrepreneurial action, with moral obligation as a moderator. Encouraging social entrepreneurship among South African youth would also help address societal issues. This is a pioneering study in the context of an emerging economy such as South Africa, where social entrepreneurship is so integral.

Considering rapid digitalization development, this study examines the impacts of digital technology innovation on social responsibility in platform enterprises.

The study applies the event study method and cross-sectional regression analysis, taking 168 digital technology innovations for social responsibility issued by 88 listed platform enterprises from 2011 to 2022 to study the impact of digital technology innovations for social responsibility announcements of different announcement content and platform attributes on the stock market value of platform enterprises.

The results show that, first, the positive stock market reaction is produced on the same day as the digital technology innovation announcement. Second, the announcement of the platform’s public social responsibility and the announcement of co-innovation and radical innovation bring more positive stock market reactions. In addition, the announcements mentioned above issued by trading platforms bring more positive stock market reactions. Finally, the social responsibility attribution characteristics of the announcement did not have a significant differentiated impact on the stock market reaction.

Most scholars have studied digital technology innovation for social responsibility through modeling rather than second-hand data to empirically examine. This study uses second-hand data with the instrumental stakeholder theory to provide a new research perspective on platform social responsibility. In addition, in order to explore the different impacts of digital technology innovation on social responsibility, this study has classified digital technology innovation for social responsibility according to its social responsibility and digital technology innovation characteristics.