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The purpose of this paper is to investigate how referral reward programs (RRPs) utilizing scarcity messages influence bank credit holders’ referrals to and adoptions by close or distant friends.

A 2×2 experiment is implemented with 760 consumers solicited through Amazon’s Mechanical Turk worker panel. Logit transformation and general linear models are used to test the proposed hypotheses.

Results showed that offering RRPs with limited available referrals (quantity scarcity) increases the overall number of referrals to and adoptions by close and distant friends. The percent of strong ties also increases with RRPs. As quantity scarcity is relaxed, the percentages of referrals to and adoptions by close friends decrease.

The inclusion of tie strength with scarcity framing greatly enhances our understanding of the effectiveness of RRPs for bank credit cards. To the authors’ knowledge, this is the first research attempt on this topic.

The purpose of this paper is to investigate how referral reward programs (RRPs) with scarcity messages influence consumer’ recommendation behavioral intentions about a bank credit card.

In total, 1,599 consumers are accessed through Amazon’s Mechanical Turk worker panel. The authors use general linear models, analysis of variance and analysis of covariance to test the proposed hypotheses.

The results showed that offering RRPs with scarcity messages increases a consumer’s behavioral intentions to recommend. The limited-quantity message in RRPs has the highest positive impact on consumers’ behavioral intentions.

No prior studies have addressed the relationship between referral rewards and scarcity messages in the bank credit card context. The study contributes to the understanding of the effectiveness of RRPs with scarcity message in improving consumer’s referral.

The purpose of this paper is to investigate how the effects of referral rewards in referral reward programs (RRPs) are moderated through perceived social risk of a recommender.

A total of 717 consumers are accessed through Amazon's Mechanical Turk worker panel. The authors use t-test and analysis of variance to test the proposed hypotheses.

The findings show that consumers with high perceived social risk balance financial rewards with social risks, while low social risk consumers largely ignore these social risk elements surrounding a referral decision.

The inclusion of perceived social risk provides the opportunity to fully understand how a consumer goes about balancing social risk and referral rewards in making referral decisions. The concept of social risk has not been previously applied to this context.

This paper aims to design a vision-based non-contact real-time accurate heart rate (HR) measurement framework for home nursing assistant.

The study applied Second-Order Blind Signal Identification (SOBI) algorithm to extract remote HR signal and analyzed it with Fast Fourier Transform (FFT). Multiple regions of interest are chosen and analyzed to obtain a more accurate result.

An accurate non-contact hear rate (HR) measurement framework is proposed and proved to be efficient.

The contributions of this HR measurement framework are as follows: accurate measurement of HR, real-time performance, robust under various scenes such as conversation, lightweight computation which is suitable and necessary for home nursing assistance. This framework is designed to be flexibly used in various real-life scenes such as domestic health assistance and affectively intelligent agents and is proved to be robust under such scenes.

This study aims to examine the influence of the quality of voluntary disclosure (QVD) on earnings management (EM) amongst a sample of commercial banks in the Middle East and North Africa (MENA) region.

Using a sample of 1,060 bank-year observations for the period 2006–2015, this paper developed a three-dimensional framework to measure the QVD, which considers the quantity, spread and usefulness of the information. Furthermore, this study examines the QVD-EM nexus using an ordinary least squares regression model. This technique is supplemented with conducting an instrumental variable regression model and a two-stage least squares model to overcome the potential occurrence of endogeneity problems.

The findings suggest that QVD is negatively attributed to EM in the context of MENA banks. The findings also confirm that the quality of financial reporting is enhanced by QVD dimensions that were considered in the framework, leading banks to less engagement in EM practices. In contrast, the influence of the quantity dimension (level) of the disclosed information has an insignificant impact on EM, while the spread and usefulness dimensions of VD are negatively and significantly associated with EM in the region.

Although the results are robust to various measurements and to the possible occurrence of endogeneity problems, there are a few limitations should be acknowledged, which provides opportunities for future research. For example, the sample size is relatively small due to data accessibility issues. Likewise, the findings of the research might not be appropriate for non-financial sectors. These limitations provide a good opportunity for future studies to expand on the research by covering other developing economies and, thereby, enriching the understanding offered by this study.

This study offers several implications for bank managers, academics and policymakers. Firstly, it may help managers to appreciate the function and the importance of QVD in mitigating EM. Secondly, for academics, the study provides suggestive evidence on the impact of QVD on EM; however, future research may need to consider the role of morality and ethical behaviour across different environments in reducing excessive risk-taking and constraining earnings manipulation. Finally, it provides insights for policymakers and regulators to develop a framework or guidance that can help banks in providing high-QVD in the context of developing economies.

The study distinctively develops an innovative measurement for QVD using a new multi-dimensional model. This paper also bring new evidence on QVD complexity and its impact on EM practice from an under-researched developing context, namely, the MENA region.

The purpose of this study is to investigate the effect of different infiltration heads on soil water movement using a free infiltration test for small-diameter tube outflow furrow irrigation under mulch film.

The test consisted of small-diameter tube outflow furrow irrigation under mulch film with three different infiltration heads (3, 4 and 5 cm) and furrow drip irrigation under mulch film using an infiltration head of 4 cm (CK).

During irrigation, the accumulated infiltration and migration distance of the wetting front increased with time. During the same infiltration time, both the accumulated infiltration and horizontal migration distance of the wetting front increased with the larger infiltration head, whereas the vertical migration distance of the wetting front gradually decreased. With increasing distance from the furrow center, soil moisture content declined, but the uniformity of its distribution increased as the infiltration head increased.

This study can provide scientific basis for the use of small-diameter tube outflow furrow irrigation under mulch film.

This paper aims to analyze the determinants of the readability non-financial disclosure prepared under the Directive 2014/95/EU in the agrifood and beverage sector.

To reach this goal, an ordinary least squares (OLS) regression model is proposed employing readability and governance variables. The sample is based on European agrifood and beverage listed firms that exceeding 500 employees and are considered public interest entities, including 744 firm-year-observations from 2017, first year after the Directive entered in force, to 2020, last year available.

The authors' results suggest the importance of corporate governance mechanisms as drivers in reaching more readability of non-financial information.

This study provides useful suggestions to policy makers and managers for a better understanding of the role played by some factors on non-financial information (NFI) readability. Moreover, findings may help regulators in confirming that the establishment of a Corporate Social Responsibility (CSR) committee is a step in the right direction to strengthening firms' NFI readability. Lastly, this is beneficial for auditors and preparers who will pay more attention to the internal factors that can push for more (or less) understandability of NFI.

This research contributes to the academic and practical debate because it adds new insights into the literature on NFI readability and represents fertile area for future researches.

Resource-based view (RBV) theory (Barney, 1991; Barney and Mackey, 2016; Nagano, 2020) states that a firm’s tangible and intangible resources can represent a sustainable competitive advantage (SCA), a long-term competitive advantage that is extremely difficult to duplicate by another firm, when it meets four criteria (i.e. not imitable, are rare, valuable and not substitutable). In the context of this case, we believe there are three sources of SCA to be discussed using RBV – the major league soccer (MLS) team player roster, the use of artificial intelligence (AI) technologies to exploit this roster and the league’s single-entity structure: • MLS players: it has been widely acknowledged that a firm’s human resource talent, which includes professional soccer players (Omondi-Ochieng, 2019), can be a source of SCA. For example, from an RBV perspective, a player on the Los Angeles Galaxy roster: > cannot play for any other team in any other league at the same time (not imitable and are rare), > would already be a competitive player, as he is acquired to play in the highest professional league in the country (valuable) and > it would be almost impossible to find a clone player matching his exact talent characteristic (not substitutable) anywhere else. Of course, the roster mix of players must be managed by a capable coach who is able to exploit these resources and win championships (Szymanski et al., 2019). Therefore, it is the strategic human resource or talent management strategies of the professional soccer team roster that will enable a team to have the potential for an SCA (Maqueira et al., 2019). • Technology: technology can also be considered a source of SCA. However, this has been a source of contention. The argument is that technology is accessible to any firm that can afford to purchase it. Logically, any MLS team (or for that matter any professional soccer team) can acquire or build an AI system. For many observers, the only obvious constraint is financial resources. As we discuss in other parts of the case study, there is a fan-based assumption that what transpired in major league baseball (MLB) may repeat in the MLS. The movie Moneyball promoted the use of sabermetrics in baseball when making talent selection (as opposed to relying exclusively on scouts), which has now evolved into the norm of using technology-centered sports analytics across all MLB teams. In short, where is the advantage when every team uses technology for talent management? However, if that is the case, why are the MLB teams continuing to use AI and now the National Basketball Association (NBA), National Football League (NFL) and National Hockey League are following suit? We believe RBV theorists have already provided early insights: > “the exploitation of physical technology in a firm often involves the use of socially complex firm resources. Several firms may all possess the same physical technology, but only one of these firms may possess the social relations, cultural traditions, etc., to fully exploit this technology to implementing strategies…. and obtain a sustained competitive advantage from exploiting their physical technology more completely than other firms” (Barney, 1991, p. 110). • MLS League Single-Entity Structure: In contrast to other professional soccer leagues, the MLS has one distinct in-built edge – its ownership structure as a single entity, that is as one legal organization. All of the MLS teams are owned by the MLS, but with franchise operators. The centralization of operations provides the MLS with formidable economies of scale such as when investing in AI technologies for teams. Additionally, this ownership structure accords it leverage in negotiations for its inputs such as for player contracts. The MLS is the single employer of all its players, fully paying all salaries except those of the three marquees “designated players.” Collectively, this edge offers the MLS unparalleled fluidity and speed as a league when implementing changes, securing stakeholder buy-ins and adjusting for tailwinds. The “socially complex firm resources” is the unique talent composition of the professional soccer team and most critically its single entity structure. While every team can theoretically purchase an AI technology talent management system, its application entails use across 30 teams with a very different, complex and unique set of player talents. The MLS single-entity structure though is the resource that supplies the stability required for this human-machine (technology) symbioses to be fully accepted by stakeholders such as players and implemented with precision and speed across the entire league. So, there exists the potential for each MLS team (and the MLS as a league) to acquire SCA even when using “generic” AI technology, as long as other complex firm factors come into play.

This case relied on information that was widely reported within media, press interviews by MLS officials, announcements by various organizations, journal articles and publicly available information on MLS. All of the names and positions, in this case, are actual persons.

MLS started as a story of dreaming large and of quixotic adventure. Back in 1990, the founders of the MLS “sold” the league in exchange for the biggest prize in world soccer – the rights to host the 1994 Fédération Internationale de Football Association World Cup before they even wrote up the business plan. Today, the MLS is the highest-level professional men’s soccer league competition in the USA. That is a major achievement in just over 25-years, as the US hosts a large professional sports market. However, MLS has been unable to attract higher broadcasting value for its matches and break into the highest tier of international professional soccer. The key reason is that MLS matches are not deemed high quality content by broadcasters. To achieve higher quality matches requires many inputs such as soccer specific stadiums, growing the fan base, attracting key investors, league integrity and strong governance, all of which MLS has successfully achieved since its inception. However, attracting high quality playing talent is a critical input the MLS does not have because the league has repeatedly cautioned that it cannot afford them yet to ensure long-term financial sustainability. In fact, to guarantee this trade-off, the MLS is one of the only professional soccer leagues with an annual salary cap. So, the question is: how does MLS increase the quality of its matches (content) using relatively low cost (low quality) talent and still be able to demand higher broadcast revenues? One strategy is for the MLS to use AI playing technology to extract higher quality playing performance from its existing talent like other sports leagues have demonstrated, such as the NFL and NBA. To implement such a radical technology-centric strategy with its players requires the MLS to navigate associated issues such as human-machine symbioses, risking fan acceptance and even altering brand valuation.

The case is written and designed for a graduate-level (MBA) class or an upper-level undergraduate class in areas such as contemporary issues in management, human resource management, talent management, strategic management, sports management and sports marketing. The case is suitable for courses that discuss strategy, talent management, human resource management and brand strategy.