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This research uses a multifaceted approach to develop an MPA/MPP curriculum to support a data science track within the existing MPA/MPP programs by identifying the core and elective areas needed.

The approach includes (1) identifying a suitable structure for MPA/MPP programs which can allow the program to develop its capacity to train students with the data science and general public administration skills to solve public policy problems and leave explicit space for local experimentation and modification; (2) defining bridging modules and required modules for the MPA/MPP programs; and (3) developing of data science track thought to make suggestions for the inclusion of suitable data science modules into the data science track and benchmarking the data science modules suggested with the best practices developed by other professional bodies. The authors review 46 NASPAA-accredited MPA/MPP programs from 40 (or 22.7%) schools to identify the suitable required modules and some potential data science and analytics courses that MPA/MPP programs currently provide as electives.

The proposal includes a three-course (six–nine credits, not counted in the program but as prerequisites) bridging module, a nine-course (27 credits) required module and a five-course (15 credits) data science track/concentration.

This work can provide a starting point for the public administration education community to develop graduate programs focusing on data science to cater to the needs of both public managers and society at large.

The purpose of this paper is to understand how hospitality companies can best explain controversial corporate social responsibility (CSR) activities to consumers who may not agree with the CSR activity. This research explores message framing through emotional and cognitive appeals to influence consumer perceptions of the Gideon Bible in USA hotel rooms. The study uses the theory of deontic justice to measure the impacts of messaging on consumer perceptions of the morality of the Gideon Bible as suicide prevention in hotels and its relation to controversial CSR initiatives.

The study uses an experimental study design via a self-administered survey to analyze participants’ perceptions of the placement of the Gideon Bible in hotel rooms and participants’ attitudes toward CSR initiatives based on deontic justice and religion using different message framing conditions.

Results show that religion was a major determinant of attitude towards the Gideon Bible, but the sentiment analysis also revealed that negative perceptions can be mitigated through message framing via emotional and cognitive appeals. Additionally, the cognitive appeal did impact CSR perceptions, as did identifying as Christian. Moral outrage emerged as a significant moderator for the relationships between message framing, attitudes toward the Gideon Bible and CSR.

This study provides an extension of deontic justice research to examine justice traits in accepting controversial CSR.

The purpose of this study is to examine the differential impact of qualitative and quantitative informational signals within the merger and acquisition (M&A) press releases on deal completion and duration. A significant percentage of deals by emerging market acquirers get abandoned before completion, and those that are completed have a longer duration. The limited information about the operations of acquirers from emerging markets creates suspicion among the stakeholders involved in deal resolution, hindering the completion of deals. Thus, using the signal-feedback paradigm, authors investigate how informational signals in the M&A press release impact the deal resolution.

The study employs content analysis on M&A press releases announced by firms from five emerging economies: Brazil, Russia, India, China and South Africa. The technique is applied based on the exploration-exploitation framework developed by March (1991) to categorize the announced deal motives (qualitative information). Next, the authors identify the percentage of relevant quantitative information disclosed in the press release, following which results are obtained using logistic and ordinary least square regressions.

The study reports that deals with declared exploratory motives take longer to complete. Additionally, deals disclosing higher percentage of quantitative disclosure exhibit lower completion rate and increased deal duration.

This is the first study to provide evidence that familiarity bias impacts deal duration as relative to exploitation deals that are familiar to the stakeholders; exploratory deals take longer to conclude. Further, our analysis indicates that a greater percentage of quantitative disclosure may not always reduce information risk but rather be interpreted negatively in the form of the acquirer’s overconfidence in the deal’s potential.

The current body of empirical research regarding the impact of trust in the cybersecurity commitment of institutions on digital payment usage has focused solely on a macro-level analysis, overlooking the intricate dynamics between institutions' cybersecurity commitments and the trust levels of digital payment users. In light of this limitation, this study aims to offer a more comprehensive understanding of this complex relationship.

A case study was conducted on digital payment users in India through the critical realist lens. To gather data, interviews and focus group discussions were conducted with digital payment users from various regions of the country.

The citizen-centric outcomes of the national cybersecurity commitment (performance and responsiveness) are the most prominent and impactful trust indicators. These outcomes play a crucial role in shaping digital payment users' perception and trust in the cybersecurity commitment of public institutions. Individuals' value positions also influence trust judgments, as it is essential to recognize the value tensions that may arise due to security implementation and their congruence with citizens' values.

The findings of this study have significant implications for policymakers. They are potentially an artifact of the security and perception of digital payment users and the cultural uniqueness of digital payment users in India.

The study proposes a holistic understanding of the relationship between institutions' cybersecurity commitments and the trust levels of digital payment users. It offers a qualitative evaluation of how digital payment users perceive and construe efficient information security management implemented by public institutions.

The goal of this work is to evaluate how digital transformation disclosure in corporate news and press releases affects stock prices. We examine American and Chinese companies from the energy and industry sectors for two periods: pre-COVID-19 and during the COVID-19 pandemic.

To estimate the effects of disclosure of information related to digital transformation, we applied the bag-of-words (BOW) method. As the benchmark dictionary, we used Kindermann et al. (2021), with the addition of original dictionaries created via Latent Dirichlet allocation (LDA) analysis. We also employed panel regression analysis and random forest.

For USA energy sector, all aspects of digital transformation were insignificant in pre-COVID-19 period, while sustainability topics became significant during the pandemic. As for the Chinese energy sector, digital strategy implementation was significant in pre-pandemic period, while digital technologies adoption and business model innovation became relevant in COVID-19 period. The results show the greater significance of digital transformation aspects for industrials sectors compared to the energy sector. The result of random forest analysis proves the efficiency of the authors’ dictionary which could be applied in practice. The developed methodology can be considered relevant.

The research contributes to the existing literature in theoretical, empirical and methodological ways. It applies signaling and information asymmetry theories to the financial markets, digital transformation being used as an instrument. The methodological contribution of this article can be described in several ways. Firstly, our data collection process differs from that in previous papers, as the data are gathered “from investor’s point of view”, i.e. we use all public information published by the company. Secondly, in addition to the use of existing dictionaries based on Kindermann et al. (2021), with our own modifications, we apply the original methodology based on LDA analysis. The empirical contribution of this research is the following. Unlike past works, we do not focus on particular technologies (Hong et al., 2023) connected with digital transformation, but try to cover all multi-dimensional aspects of the transformational process and aim to discover the most significant one.

Both the SEC (Securities and Exchange Commission) and the popular press have routinely criticized firms for the complexity of their financial disclosures. This study aims to investigate how financial analysts respond to the tone complexity of firm disclosures.

Using approximately 20,000 earnings conference call transcripts of S&P 1,500 firms between 2005 and 2015, the authors first calculate the abnormal negative tone, the measure of tone complexity; then use such tone measure in econometric models to examine analyst forecast behavior. The authors also test the robustness of the results under different model specifications, tone word lists and alternative tone measure calculations.

Consistent with the notion that analysts respond to the information demand from investors and incur more costs and effort to analyze firm disclosure when the tone is more complex, the authors find that higher tone complexity is positively and significantly associated with more analyst following, longer report duration, more forecast revisions, larger forecast error and larger forecast dispersion. In addition, the authors find that tone complexity has a long-term impact on analyst following but has a limited long-term impact on analyst report duration, analyst revision, forecast error and dispersion.

This study complements existing literature by highlighting the information role of financial analysts and by providing evidence that analysts incorporate the management tone disclosed during conference calls to adjust their forecasting behaviors. The results can be used by policymakers as evidence and support for further improving firm communication from a new dimension of disclosure tone.

Cyber-attacks that generate technical disruptions in organisational operations and damage the reputation of organisations have become all too common in the contemporary organisation. This paper explores the reputation repair strategies undertaken by organisations in the event of becoming victims of cyber-attacks.

For developing the authors’ contribution in the context of the Internet service providers' industry, the authors draw on a qualitative case study of TalkTalk, a British telecommunications company providing business to business (B2B) and business to customer (B2C) Internet services, which was a victim of a “significant and sustained” cyber-attack in October 2015. Data for the enquiry is sourced from publicly available archival documents such as newspaper articles, press releases, podcasts and parliamentary hearings on the TalkTalk cyber-attack.

The findings suggest a dynamic interplay of technical and rhetorical responses in dealing with cyber-attacks. This plays out in the form of marshalling communication and mortification techniques, bolstering image and riding on leader reputation, which serially combine to strategically orchestrate reputational repair and stigma erasure in the event of a cyber-attack.

Analysing a prototypical case of an organisation in dire straits following a cyber-attack, the paper provides a systematic characterisation of the setting-in-motion of strategic responses to manage, revamp and ameliorate damaged reputation during cyber-attacks, which tend to negatively shape the evaluative perceptions of the organisation's salient audience.

This study aims to understand the extent of privacy concerns regarding voice-activated personal assistants (VAPAs) on Twitter. It investigates three key areas: (1) the effect of privacy-related press coverage on public sentiment and discussion volume; (2) the comparative negativity of privacy-focused conversations versus general conversations; and (3) the specific privacy-related topics that arise most frequently and their impact on sentiment and discussion volume.

A dataset of 441,427 tweets mentioning Amazon Alexa, Google Assistant, and Apple Siri from July 1, 2019 to June 30, 2021 were collected. Privacy-related press coverage has also been monitored. Sentiment analysis was conducted using the dictionary-based software LIWC and VADER, whereas text mining packages in R were used to identify privacy-related issues.

Negative privacy-related news significantly increases both negativity and volume in Twitter conversations, whereas positive news only boosts volume. Privacy-related tweets were notably more negative than general tweets. Specific keywords were found to either increase or decrease the sentiment and discussion volume. Additionally, a temporal evolution in sentiment, with general attitudes toward VAPAs becoming more positive, but privacy-specific discussions becoming more negative was observed.

This research augments the existing online privacy literature by employing text mining methodologies to gauge consumer sentiments regarding privacy concerns linked to VAPAs, a topic currently underexplored. Furthermore, this research uniquely integrates established theories from privacy calculus and social contract theory to deepen our analysis.

Just like human beings, some companies engage in recurrent bad behaviour that negatively impacts their stakeholders and their prospects for long-term survival. For example, some firms become caught up in a vortex of corruption. SNC-Lavalin, a large Canadian consulting engineering company, is an example of one organisation that embarked on this path. Since then, the company has taken numerous steps to overcome its persistent problems with corruption. The object of this study is to determine whether these steps can be compared to the 12-step program of Alcoholics Anonymous (AA), which is recognised for helping individuals overcome addiction to alcohol and drugs.

To examine events at SNC-Lavalin between 2000 and 2022, the authors carry out an in-depth examination of internal and external documentation. Three sources of data are used: archival documents, news articles and corporate documentation.

The results of the analysis show that the AA 12-step program seems to correspond to the steps SNC-Lavalin has taken over time. The “organisational” version of this program that the authors have developed could be useful to advisers of companies that are struggling with other types of bad behaviour and wish to stamp it out. These bad behaviours include the exploitation of vulnerable manpower, the exploitation of consumers through planned obsolescence or aggressive sales practices and pollution in all its forms.

The study has certain limitations. It should be noted that the analyses were limited to public information. In addition, given the quantity of public information available for the period from 2009 to 2022, a methodical approach to selecting the sources of information elements was applied, which inevitably entailed ignoring other sources of information (e.g. television, radio and internet).

This study adds to previous work by providing an original and global perspective of the steps taken by a large international consulting engineering firm to overcome its recurring corruption problems. The parallel drawn with AA’s 12-step programs seems to correspond surprisingly well to the steps taken by the company. This parallel can potentially serve as a roadmap for advisers who have to counsel companies on recurring misconduct that has harmful repercussions for their stakeholders.

The purpose of this paper is to focus on managing the risk of fraud in commercial letters of credit (LC) in Bangladesh involving three parties: the seller, the buyer and the bank. It addresses the severity of LC fraud, the banks’ actions when detected and the preventive measures the relevant parties can adopt.

This research uses doctrinal and qualitative methods to propose strategic actions that benefit buyers, sellers, banks, legal professionals and judges. The study aims to explore the modus operandi used by fraudsters through thematic analysis.

The study’s findings reveal that LC fraud has escalated to a concerning level, posing a significant threat to the economic stability of Bangladesh. Measures must be taken to mitigate this risk and safeguard the country’s financial integrity. To effectively combat the risk of LC fraud, the updated version of UCP must include specific and detailed guidelines on LC fraud. This study recommends preventative measures that all parties involved must take to reduce the likelihood of fraud significantly.

Due to a lack of LC experts, the participant sample for the study in Bangladesh was limited. Nevertheless, most banking participants were highly distinguished and held the Head of Trade Finance Department position in commercial banks. A few academics and legal practitioners with LC expertise also participated in the study.

It provides cutting-edge solutions to effectively handle LC fraud risk and provides proactive measures to prevent it.