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Relative performance evaluation (RPE) intensifies competitive pressure by tying executive compensation to the profits of rivals. We show that these contracts make loan syndication harder by reducing banks' willingness to participate in loans underwritten by banks named in their RPE contracts. Lead arranger banks, which are more frequently named in RPE, hold larger shares of the loans they syndicate, and their borrowers receive smaller and fewer loans and face higher spreads. Our results highlight the tension between the normal benefits of competition versus the need for cooperation in loan syndication. [ABSTRACT FROM AUTHOR]

To overcome product homogenisation issues, an increasing number of supply chain members have been binding their competitive advantages to services which extend supply chain competition to a new dimension. This paper proposes a product service supply chain (PSSC) network competition model with multiple competing manufacturers and retailers offering demand-enhancing and costly services. In order to obtain the decision-making results in a non-cooperative game context, equilibrium conditions are established using variational inequality, and the qualitative properties are discussed. We compare the two competition scenarios, price competition only and simultaneous price and service competition, to discover the impact of service-offering on supply chain members. After introducing the service competition, both manufacturers and retailers realise higher profits and marginal profits with the same service costs. In contrast, the manufacturers' marginal profits achieve higher growth rates. We also find that (a) the increase of the demand sensitivities to the service levels of retailers would contribute more to the revenue growth of the whole PSSC network and (b) when service costs are different for manufacturers and retailers, the optimal decision-making on service levels are not only affected by the service costs of the members in the same tier but also correlated with those in other tiers. [ABSTRACT FROM AUTHOR]

The challenges encapsulated in the 'War for Sales Talent' are symbolic of the struggles inherent in the recruitment, nurturing, and retention of sales professionals. While extant research provides valuable insights into facets like hiring practices, selection criteria, coaching, and training strategies, a noticeable void persists in guiding salespeople as they navigate beyond the initial ramp-up period in a new role. By interconnecting survey responses from a cohort of 200 service salespeople with 18–24 months of tenure, this investigation brings to light the facets of effort—encompassing prospecting, conversion, retention, and growth—that exert an influence on the change in year-over-year revenue following a salesperson's first complete sales cycle post-onboarding. The results underscore the significance of conversion and growth efforts, revealing their robust impact on the net change in sales revenue. In challenging existing paradigms, this study proposes a conceptual shift in understanding sales effort. Rather than adhering to the prevailing unidimensional viewpoint, the findings advocate for recognizing sales effort as a multi-dimensional construct with competing demands. This nuanced perspective contributes to a more comprehensive understanding of the factors influencing revenue growth for salespeople transitioning from the ramp-up period toward a sustainable, growth-oriented trajectory. [ABSTRACT FROM AUTHOR]

This study examines the importance of governance quality of local government in small businesses' future revenue growth forecasting accuracy. Forecasting errors are due to either overestimation or under-estimation. When local governance quality improves, transaction costs are eliminated, boosting firms' actual performance up to the level forecast, thereby reducing overestimation. Also, when local governance quality improves, institutional trust (trust in government) and generalized trust (trust in strangers) improve, lifting the expectation of future performance to the actual level, thereby reducing under-estimation. We investigate these two mechanisms using a set of more than 250,000 small businesses in Vietnam using an instrumental variable approach to control for potential endogeneity. It is found that governance quality enhances forecasting accuracy by reducing under-estimation forecasting errors but, interestingly, without affecting overestimation errors. This paper is one of the first that links governance quality to business forecasting, indicating that local authorities can help local businesses make efficient resource preparation by improving their governance quality. [ABSTRACT FROM AUTHOR]

This article examines how collective bargaining through unions and workplace codetermination through works councils relate to labor market imperfections and how labor market imperfections relate to employer wage premia. Based on representative German plant data for the years 1999–2016, the authors document that 70% of employers pay wages below the marginal revenue product of labor and 30% pay wages above that level. Findings further show that the prevalence of wage markdowns is significantly smaller when organized labor is present, and that the ratio of wages to the marginal revenue product of labor is significantly larger. Finally, the authors document a close link between labor market imperfections and mean employer wage premia, that is, wage differences between employers corrected for worker sorting. [ABSTRACT FROM AUTHOR]

Despite scholarly critiques, use of the Net Promoter Score (NPS®) continues to grow in popularity among firms. Even researchers who criticize NPS recognize its potential for predicting desirable customer behaviors and revenue growth. However, a firm's goal in measuring NPS is not to simply assess it, but to be empowered to improve that score. This goal begs an important question: Does a "net promoter" study provide the insights that a firm needs to improve their NPS? The critical, but untested, assumption in NPS use is that the insights gained from open-ended customer comments in a net promoter study can be used to set improvement priorities that will increase future NPS likely-to-recommend ratings. Through two distinct studies, one in a business-to-business context with auto dealership decision-makers and one in a business-to-consumer context with vehicle repair customers, we investigate this assumption. Our results reveal that the critical untested assumption of a net promoter study is questionable. The convergence is low to moderate between open-ended priorities from a net promoter study and predictors of the standard 'likely-to-recommend' NPS question. We also find that the convergence between customers' open-ended priorities and their stated and derived priorities from closed-ended responses is higher for NPS detractors and passives than promoters, but it is still only moderate. The strength of this convergence of priorities is also impacted by the wording of the questions used to elicit customers' open-ended priorities. Firms using open-ended comments to set priorities should ask customers, especially detractors, to identify areas for improvement. In addition, they should supplement open-ended customer feedback with closed-ended questions to get customers' performance ratings in relation to their specific needs. [ABSTRACT FROM AUTHOR]

We demonstrate that investors in initial public offering (IPO) firms value revenues and that the number of U.S. Securities and Exchange Commission (SEC) revenue recognition comment letters issued on the S-1 registration statement are positively associated with reported revenues. We also find that IPO managers report revenues opportunistically in the fiscal year just prior to the offer. In additional analysis, we find that discretionary revenues are associated with significantly higher first day IPO stock returns but significantly lower 1 year stock returns. Our results are consistent with the incentives of managers to report revenues opportunistically outweighing the higher monitoring and regulatory scrutiny pre-IPO. [ABSTRACT FROM AUTHOR]

Since we wrote "Crowdsourcing as a solution to distant search" a decade ago, enthusiasm for crowdsourcing's capacity to produce remarkable solutions to some problems has continued to grow, and profiting from crowdsourced solutions has become a strategic goal for more and more firms. Crowdsourcing research has progressed impressively, with more progress made in researching the phenomenon than in theorizing about it. We are deeply honored by the 2022 Decade Award. In this manuscript, we reflect on the factors that led to this progress in crowdsourcing research, and how the theoretical insights from our paper––e.g., markets in the hierarchies-markets dichotomy are made up of markets with ex ante contracts and crowdsourcing (markets with no ex ante contracts)––may have influenced that progress. Also, because profits have become the ultimate goal of a large number of the seekers of solutions through crowdsourcing, we present an outline of a framework for exploring the impact of crowdsourcing on a seeker's profitability. The framework builds on insights from the paper and new constructs in crowdsourcing such as artificial intelligence (AI), the crowdsourcing process, revenue models, complementary assets, and organizing to minimize crowdsourcing disadvantages that we have added. We conclude with suggestions for future research. [ABSTRACT FROM AUTHOR]

Research Summary: This study abductively investigates how a firm's degree of business model development—the extent to which strategic choices are crystallized—moderates the impact of a scientific approach to decision‐making on performance. We present findings from a field experiment involving 261 entrepreneurs, where treated entrepreneurs learn to apply a scientific approach, while control counterparts receive comparable content without this approach. Results show that the effect of scientific decision making varies with business model development. Treated entrepreneurs with higher degrees of business model development elaborated their theories of value focusing on lower‐level choices, achieving superior economic performance compared to controls. Conversely, treated entrepreneurs with lower levels of business model development reevaluated fundamental aspects, resulting in increased epistemic uncertainty and less favorable short‐term economic outcomes compared to controls. Using a field experiment with 261 entrepreneurs, we explored how the degree of business strategy definition influences the benefits of adopting a scientific approach to decision‐making. In the experiment, half of the entrepreneurs were taught to use a scientific approach for making decisions (the treated group), while the others received similar training without the scientific approach (the control group). Results show that treated entrepreneurs with already defined strategies benefited more, experiencing improved performance even in the short term. Conversely, treated entrepreneurs with strategies still under definition experienced more uncertainty and lower short‐term economic performance, as the scientific approach prompted them to reassess and adjust their core strategic decisions. [ABSTRACT FROM AUTHOR]

To investigate the relationship between Chinese university funding and academic output, we collected data on the scale and the structure of funding and academic output of 36 World-Class universities under construction in China during 2013–21 and 2014–22. Furthermore, we empirically analyzed the effects of funding scale and structure on academic output using ordinary least squares (OLS) regression, random effects, and fixed effects models. This study demonstrates that the scale and structure of funding have a significant effect on academic output. Among them, the scale of total budget revenue has a significant effect on academic output, and its influence on highly-cited researchers (HiCi) is greater than the other indicators. The scale of total budget expenditure also has a significant positive influence on academic output, and its influence on N&S is greater than the other indicators in order. The structure of revenue has a significant influence on academic output, and business revenue has the greatest influence on PUB. The structure of horizontal expenditure has a significant influence on academic output. The vertical expenditure structure has a significant impact on academic output, and educational expenditure has the greatest impact on PUB. Based on the results, we discuss implications for researchers and for policymakers to improve the construction effect of World-Class universities under construction in China. [ABSTRACT FROM AUTHOR]

The increase in the demand for seaweed biomass and high-quality products has created an urgent need for a more productive and sustainable cultivation system. Deep seawater (DSW) is rich in inorganic nutrients, unpolluted, and has low-temperature stability. Small-scale industries utilising DSW have been established, with DSW being employed for bottled drinking water, aquaculture, agriculture, cosmetics, medicine, food, and power generation—all contributing to substantial economic benefits. DSW has also been used for seaweed farming, where its high nutrient levels have increased biomass yield and biochemical composition while reducing fertiliser expenditures. Ocean thermal energy conversion (OTEC) is an emerging technology for renewable energy production. The DSW drawn up to generate energy through the temperature difference between the cold DSW and the warm surface seawater can be used for diverse applications, including seaweed cultivation. In warm tropical regions, the cold DSW can be used to manipulate the temperature of seawater to extend the range of temperate high-value seaweeds into the tropics. Malaysia has been identified as suitable for OTEC development, especially in Sabah. An ongoing OTEC research project between Malaysia and Japan includes research on value creation from the OTEC DSW through the cultivation of abalone and seaweeds. It is timely for a comprehensive review of the advantages of using DSW for seaweed farming and how the integration of this innovative technology with the OTEC system can provide value-added products and revenue to both industries, which are important components of the emerging blue economy. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic made hotels around the world to experience a huge drop in revenues as lockdowns restricted mobility. For many hotel operators, the rent of the building is one of the most important fixed costs. The Rebus Sic Stantibus clause allows judges to rule that changes can be made to the economic conditions of contracts when a supervening event, not foreseen by the parties, causes economic hardship. This paper analyses, considering different market structures and the degree of product differentiation, how the rent for hotel facilities agreed in long-term contracts will change if the clause is applied now, reducing by law current rents. JEL Classifications : K12, K22, D43, L83 [ABSTRACT FROM AUTHOR]

It is a common practice that business and economy compartments share the seating capacity of a short or medium-haul European flight, with the middle seats in the business compartment kept vacant to enhance comfort and privacy for business passengers. The two compartments are separated by a movable curtain whose position determines the capacity allocated to each compartment. By postponing the decision on curtain position until departure, airlines gain extra flexibility in their capacity allocation. We formulate an airline's problem of dynamically determining the curtain position and the subset of fare products to offer in each compartment to maximize the combined revenue from business and economy passengers. We show that the airline should offer a business (resp., economy) fare product if and only if its fare exceeds a business (resp., economy) threshold or bid price. We then establish monotonicity properties which are useful in expediting the computation of the optimal policy. An extended model where the airline has the option to offer a free upgrade (from economy to business class) to a new arriving economy passenger is presented, and a necessary condition on when to offer upgrades is provided. Using a large-scale and real-life case study based on a proprietary dataset, we demonstrate significant revenue improvements from postponing the decision on curtain position, compared to the current practice of fixing it at the beginning of the booking horizon. Furthermore, we provide guidance for the implementation of our policy, taking into account passengers' seat selection and substitution towards lower fare classes. We also discuss the implications of our work in practice. [ABSTRACT FROM AUTHOR]

We study the licensing of a cost-reducing innovation in a Cournot oligopoly where an outside innovator uses three part tariffs that are combinations of upfront fees, per unit royalties and ad valorem royalties. Under general demand, the maximum possible licensing revenue under three part tariffs can be always attained by a policy that uses at most two of the three components. For relatively significant innovations, there exists an optimal policy consisting of a per unit royalty and upfront fee and a continuum of other optimal policies that are three part tariffs whose all components are positive. Completely characterizing optimal policies under linear demand, we show that for oligopolies with four or more firms: (i) pure upfront fees are optimal for insignificant innovations; (ii) for intermediate and significant innovations: (a) there is a continuum of optimal policies which always includes a two part tariff with a unit royalty and upfront fee and (b) a two part tariff with an ad valorem royalty and fee or a two part royalty can be optimal for some, but not all parametric configurations. [ABSTRACT FROM AUTHOR]

Intercropping is proposed as a promising strategy to meet future food demand while reducing agriculture's environmental impact by re-diversifying agricultural fields. Strip cropping, a form of intercropping, has a potential to simultaneously deliver multiple ecosystem services including productivity, while facilitating management as strip width can be adjusted to the working width of available machines. While the yield performance of strip cropping systems is influenced by the interaction between neighboring crops, to date, empirical studies on the performance of various crop combinations in strip cropping systems are limited. Here we used three-year data (2020–2022) from a 64-ha organic strip cropping system in the Netherlands to (1) evaluate the effects of crop neighbors and strip cropping on yield and (2) explore if optimizing the allocation of crop neighbors in alternative strip cropping configurations can improve yield and revenue performances. We analyzed the edge effect and strip cropping effect on yield of six crops grown in strips, each neighboring a total of five crops. The yield data was then used to evaluate the performance of the current and alternative strip configurations in terms of LER and relative revenue. Results showed that except for the positive effect observed on potato when neighboring celeriac or broccoli, edge effects lacked statistical significance. Strip cropping effect varied per crop: positive for faba bean and parsnip, neutral for celeriac and potato, and negative for oat and onion. Analysis across crops showed an overall significant positive strip cropping effect on yield. These findings highlighted the value of analysis at the cropping system level in developing designs aimed at unlocking the potential of strip cropping. The positive but variable strip cropping effects observed in the current experimental design and the two alternative configurations suggests prioritizing an overall increased crop diversity over optimizing their spatial arrangement. While we demonstrated increased productivity with strip cropping, further research is needed to expand the database on optimal crop combinations, extending the evaluation beyond yield and revenue performances to facilitate broader adoption of strip cropping in the Netherlands and Western Europe. [ABSTRACT FROM AUTHOR]

In the spatial public goods game (SPGG), punishment effectively promotes cooperation but often reduces the collective benefits of cooperators and punishers. In order to increase revenue, we propose a probabilistic interaction domain model considering both strategy type and payoff level. In this model, players are divided into two types, successful players with payoffs higher than the payoff threshold and failed players with payoffs lower than the payoff threshold. A successful player is less likely to change the interaction range than a failed player. Through extensive simulations, it is shown to verify that a higher payoff threshold leads to a more pronounced promotion effect on cooperation and corresponds to a higher cooperation return. Moreover, introducing dynamic interaction domain can rapidly remove defectors from the vicinity of cooperative players on regular lattices. Reducing the payoff gap between punishers and cooperators helps mitigate the system's second-order free-riding problem. Additionally, through analysis of the critical parameters, it is revised that incorporating diversity in interaction structures substantively enhances cooperation level. [ABSTRACT FROM AUTHOR]

The design of data markets has gained importance as firms increasingly use machine learning models fueled by externally acquired training data. A key consideration is the externalities firms face when data, though inherently freely replicable, is allocated to competing firms. In this setting, we demonstrate that a data seller's optimal revenue increases as firms can pay to prevent allocations to others. To do so, we first reduce the combinatorial problem of allocating and pricing multiple datasets to the auction of a single digital good by modeling utility for data through the increase in prediction accuracy it provides. We then derive welfare and revenue maximizing mechanisms, highlighting how the form of firms' private information – whether the externalities one exerts on others is known, or vice-versa – affects the resulting structures. In all cases, under appropriate assumptions, the optimal allocation rule is a single threshold per firm, where either all data is allocated or none is. [ABSTRACT FROM AUTHOR]

Over the past two decades, tax nudging has gained popularity as a method to boost tax compliance and help revenue authorities increase tax collection. However, most evidence on the effect of behaviourally informed tax letters comes from environments with high administrative capacity, which raises doubts about its generalizability. Against this background, this article tests the compliance effect of including messages that trigger deterrence or reciprocity beliefs in tax letters through a randomized controlled trial implemented in two mid‐sized Mozambican municipalities, Vilankulo and Dondo. Conducted in 2018, the experiment focuses on property taxation, a tax overwhelmingly perceived to perform well below its potential in many low‐ and middle‐income countries. The analysis relies on administrative data and exploits the complete universe of registered property tax taxpayers, including individuals and enterprises. The results indicate that (i) receiving a notification letter – not necessarily common practice in many contexts – has a significant positive impact on compliance; (ii) among enterprises, the message alluding to reciprocity backfires, while the most effective message to include generally is the one alluding to deterrence; and (iii) previously compliant taxpayers react negatively to the letter, regardless of the message included. These results carry relevant policy implications, indicating the large scope for behaviourally informed letters to help increase tax compliance, even in low administrative capacity settings. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic affected most companies' profits negatively, but some companies did exceptionally well, recording excess profits during the pandemic. In this paper, we estimate the scale of the excess profits and the tax revenue potential of an excess profits tax, an additional tax levied by governments on companies' excess profits. To estimate excess profits, we develop a trend-adjusted average earnings methodology. We apply the methodology to firm-level consolidated Orbis data to estimate that large multinational corporations with subsidiaries in the EU generated excess profits of $447 billion in 2020 (42% of their total profits in 2020). Using country-by-country reporting data, we estimate the excess profits arising from each EU member state and find that EU member states could together raise $6 billion with an excess profits tax of 10%. [ABSTRACT FROM AUTHOR]

Tax collection with limited enforcement capacity may be consistent with both high- and low-delinquency regimes: high delinquency reduces the effectiveness of threats, thereby reinforcing high delinquency. We explore the practical challenges of unraveling the high-delinquency equilibrium using a mechanism design insight known as divide-and-conquer. Our preferred mechanism takes the form of prioritized iterative enforcement (PIE). Taxpayers are ranked using the ratio of expected collection to capacity use. Collection threats are issued in small batches to ensure high credibility and induce high compliance. Following repayments, liberated capacity is used to issue the next round of threats. In collaboration with a district of Lima, we experimentally assess PIE in a sample of 13,432 property taxpayers. The data validate and refine our theoretical framework. A semi-structural model suggests that keeping collection actions fixed, PIE would increase tax revenue by roughly 10%. [ABSTRACT FROM AUTHOR]

Recommendation systems are crucial in boosting companies' revenues by implementing various strategies to engage customers and encourage them to invest in products or services. Businesses constantly desire to enhance these systems through different approaches. One effective method involves using hybrid recommendation systems, known for their ability to create high-performance models. We introduce a hybrid recommendation system that leverages two types of recommendation systems: first, a novel deep learning-based recommendation system that utilizes users' and items' content data, and second, a traditional recommendation system that employs users' past behaviour data. We introduce a novel deep learning-based recommendation system called convolutional autoencoder recommendation system (CAERS). It uses a convolutional autoencoder (CAE) to capture high-order meaningful relationships between users' and items' content information and decode them to predict ratings. Subsequently, we design a traditional model-based collaborative filtering recommendation system (CF) that leverages users' past behaviour data, utilizing singular value decomposition (SVD). Finally, in the last step, we combine the two method's predictions with linear regression. We determine the optimal weight for each prediction generated by the collaborative filtering and the deep learning-based recommendation system. Our main objective is to introduce a hybrid model called CAERS-CF that leverages the strengths of the two mentioned approaches. For experimental purposes, we utilize two movie datasets to showcase the performance of CAERS-CF. Our model outperforms each constituent model individually and other state-of-the-art deep learning or hybrid models. Across both datasets, the hybrid CAERS-CF model demonstrates an average RMSE improvement of approximately 3.70% and an average MAE improvement of approximately 5.96% compared to the next best models. [ABSTRACT FROM AUTHOR]

Carbon prices have grown remarkably in the European Union (EU) Emissions Trading System (ETS) in recent years, raising distributional concerns. Revenues are expected to grow with higher carbon prices, thus providing resources to address distributional issues. Beyond a certain point, however, higher prices can discourage the purchase of allowances and ultimately reduce revenues, describing a Carbon Laffer Curve (CLC). We empirically investigate the CLC in the EU ETS between 2012 and 2021 using auction revenues at the country level. Results indicate that ETS revenues follow an inverted‐U relationship in both the volume and the price of auctioned allowances, with an estimated optimal price between 86 and 125 euros. [ABSTRACT FROM AUTHOR]

Purpose: Netflix is the market leader in the streaming entertainment industry. In 2020 and 2021, Netflix's subscriber numbers and revenue increased. During the first two quarters of 2022, Netflix lost millions of subscribers, revenue and profit declined and its share price and market capitalization deteriorated. The purpose of this study is to investigate how and why a company with such a strong track record as Netflix can experience this crisis and, most importantly, how it overcame the crisis and returned to growth. Design/methodology/approach: This case study investigates Netflix's rise, fall and recovery between 2020 and 2023 using qualitative research methods. It examines earnings calls, transcripts and letters to shareholders as well as the views of investment analysts, journalists and academics. Findings: Netflix turned its fortunes around because its leaders faced the crisis head-on. They acknowledged that previous strategic decisions were no longer working, that no advertisements were on the platform and that there was no account sharing and they reversed these decisions. Netflix also realized that it needed to innovate, so it partnered with Microsoft to execute its go-to-market with advertising. It also launched games, made strategic acquisitions of gaming studios and developed its capabilities with new products. Originality/value: This is a valuable case study. Investigating how a company as successful as Netflix can encounter a severe decline and how it changed its strategies and tactics to reverse the decline provides important lessons for other companies. [ABSTRACT FROM AUTHOR]

Drawing on human capital theory, we explore the impact of global mobility on individuals and their employing firms. We also investigate the role of cultural distance between workers who move across country borders and the local culture, and the role that HRM may play to improve capitalizing on global talent mobility. We use a big data set comprising the entire population in one country, including about 30,000 expatriates from 143 countries employed by 15,000 firms, over 11 years of data covering about 100,000 observations on expatriates and 80,000 on their firms. Our findings support the existence of positive impact of global firms on performance (6.7% higher revenues after labor costs) and individuals' wages (10%–20% higher salaries). Both relationships are statistically and economically significantly influenced by cultural distance for the performance of global firms, leading to HRM implications. [ABSTRACT FROM AUTHOR]

Frequent occurrence of disruptions in the supply chain due to the Covid-19 pandemic has increased the supply chain vulnerability (SCU), which affects the performance and revenue generation of firms. If the commodity we are dealing with in a supply chain is of a perishable nature, then the situation becomes more complicated, as such products need restrictive storage and transportation facilities. The dairy supply chain is one such perishable product supply chain. This paper, thus, proposes a method to identify key drivers of SCU in a dairy SC followed by establishing a model using interpretive structural modeling (ISM) and a graph theory approach (GTA) to calculate the SCU Index. It is important to quantify the SCU for identifying major factors affecting it and then developing techniques to mitigate it. In order to quantify the SCU, first, the ISM model is used to identify the interrelation between drivers, and then an adjacency matrix is formed by using the interdependence, thereby adding inheritance of each driver. A variable permanent matrix is formed to calculate the SCU Index for the SC. This proposed approach will help managers in mitigating the adverse effects of COVID-19 on the dairy supply chain. [ABSTRACT FROM AUTHOR]

While our understanding of the relationships between revenue diversification and nonprofit financial health has deepened over the past three decades, little is known about the association between revenue diversification and nonprofit mission performance. Moreover, there is an ongoing debate as to whether revenue diversification hinders or improves nonprofit performance. Some expect performance improvement from diversification strategies, while others contend that concentration strategies drive performance. This study aims to fill this research gap by investigating the effect of revenue diversification on nonprofit managers' perceived mission performance. Using data from a sample of Taiwan's human service nonprofits collected in 2020, we estimate relationships with regressions, employing a more detailed measure of organizational performance and various revenue diversification measurements. The results suggest that revenue diversification is positively associated with nonprofit managers' perceived mission performance. This study further discusses theoretical contributions to the literature and practical implications for human service nonprofit organizations. [ABSTRACT FROM AUTHOR]

Despite the advent of trade liberalisation, trade taxes still remain a key source of tax revenues in sub‐Saharan Africa. Further trade reforms in the form of the African Continental Free Trade Area could, however, hinder output growth in the region if these reforms lead to a decline in total tax revenues. Motivated by this conundrum, this paper investigates the impact of trade liberalisation on tax revenues across a panel of sub‐Saharan African countries. The results indicate that trade liberalisation is associated with an increase in total tax revenues. Also, the reduction of import and export duties significantly increases and decreases domestic and trade tax revenues, respectively. In addition, greater urbanisation is associated with an increase in total tax revenues, while inflation decreases tax revenues. [ABSTRACT FROM AUTHOR]

Problem definition: How can retailers incentivize customers to make healthier food choices? Price, convenience, and taste are known to be among the main drivers behind such choices. Unfortunately, healthier food options are often expensive and not adequately promoted. However, we are observing recent efforts to nudge customers toward healthier food. Methodology/results: In this paper, we conducted a field experiment with a global convenience store chain to better understand how different add-on bundle promotions influence healthy food choices. We considered three types of add-on bundles sequentially: (i) an unhealthy bundle (when customers purchased a coffee, they could add a pastry for $1), (ii) a healthy bundle (offering a healthy snack, such as fruit, vegetable, or protein, as a coffee add-on for $1), and (iii) a choice bundle (the option of either a pastry or a healthy snack as an add-on to coffee for $1). In addition to our field experiment, we conducted an online laboratory study to strengthen the validity of our results. Managerial implications: We found that offering healthy snacks as part of an add-on bundle significantly increased healthy purchases (and decreased unhealthy purchases). Surprisingly, this finding continued to hold for the choice bundle, that is, even when unhealthy snacks were concurrently on promotion. However, we did not observe a long-term stickiness effect, meaning that customers returned to their original (unhealthy) purchase patterns once the healthy or choice bundle was discontinued. Finally, we show that offering an add-on choice bundle is also beneficial for retailers, who can earn higher revenue and profit. Funding: This research was supported by the James McGill Scholar Award Fund, the Scale AI Chair Program, IIVADO (Institut de valorisation des données) Fundamental Research Project Grant, and two Discovery Grants from the Natural Sciences and Engineering Research Council of Canada. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.0336. [ABSTRACT FROM AUTHOR]

Improving the supply efficiency of ecological products (EPSE) is of great significance to protect the ecological environment, promote the development of green industry and the sustainable growth of the economy. This paper focuses on constructing an evaluation index system for EPSE and exploring the relationship between the development level of the digital economy (DE) and EPSE in China. To measure the EPSE, the study employs the Undesirable Slacks-Based Measurement (SBM) Model across 30 provinces, cities and districts in China from 2011 to 2022. Furthermore, the research utilizes spatial econometric models, panel threshold effect models, and other methodologies to investigate the impact mechanism and nonlinear relationship between DE and EPSE. The research shows that: (1) The overall level of EPSE in the study area is relatively low, with significant development differences observed; (2) The DE has a nota-ble spatial spillover effect on EPSE, with a significantly negative impact in neighboring areas; (3) The development of the DE promotes EPSE through the upgrading of human capital structure, industrial structure, and increases in local government fiscal revenue and corporate operating profits; (4) Heterogeneity analysis shows that the impact of DE on EPSE varies significantly across eastern, central, and western China, with positive effects pronounced in the eastern and western regions; (5) Regression results of the threshold effect indicate a significant single threshold effect on the impact of DE development level on EPSE. Specifically, when the threshold value is less than 0.1232, DE significantly contributes to the improvement of EPSE. This paper contributes new literature evidence and factual references to the understanding of the causal relationship between DE and EPSE. The findings highlight the importance of considering spatial spillover effects, impact mechanisms, and regional heterogeneity in analyzing the relationship between DE and EPSE. The research also suggests that promoting the development of the digital economy could be a viable strategy to enhance EPSE, especially in regions where the threshold value is below 0.1232 [ABSTRACT FROM AUTHOR]

Introduction: Price competition in the tomato market may lead Italian processing companies to adopt product differentiation strategies to attract consumers and raise revenues. Exploring consumers' preferences for processed tomato products' attributes can support companies in implementing product differentiation strategies and succeed in the market. Methods: This study used a convenience sample of 602 Italian consumers to identify consumers' preferences for processed tomato products' attributes selected through a literature review and tested by the Best Worst Scaling (BWS) method. Also, a two-step cluster analysis was used to identify and size consumer groups with common preferences for tested product's attributes. Results: Overall, our results showed that Italian consumers of processed tomato products strongly preferred attributes such as Country of origin, Organic, and Social and economic sustainability labels. In addition, the analysis shows the existence of three distinct consumer segments such as "traditional," "pricesensitive," and "sustainable" consumers. The largest one was price-sensitive consumers followed by sustainable and traditional ones. Discussion: Our findings have practical implications for producers and policymakers. Producers may use claims about the product's origin jointly with an organic production logo and ethical label to differentiate their products and raise revenues. Likewise, policymakers should enhance monitoring and control measures to ensure with environmental, social, and economic sustainable standards compliance. This will support building consumer trust for those credence attributes. Overall, this study adds valuable insights to the existing literature on consumer preferences for processed tomato products, providing results with high external validity using a large convenience sample. [ABSTRACT FROM AUTHOR]

Investigator-initiated clinical studies (IICSs), also referred to as non-commercial, academic or independent clinical studies, address important research questions that are usually neglected by industry despite their high societal value. Indeed, industry may direct their focus and resources on studies that will yield results and products that can ultimately generate revenue for the company. Conversely, IICS research questions include (a) refining or getting new indications of available treatments (drug repurposing); (b) optimisation, by comparing various health products or treatment regimens; and (c) innovation, especially for advanced therapies. Multinational IICSs increase the scientific quality of the data by exchange of research ideas, scientific techniques and tools. Participation of patients from different geographical, social and ethnic backgrounds equally adds to the value of study results and yields more generalisable evidence than a study confined to a single geographical location. Multinational IICSs are generally sponsored by non-profit/academic organisations and publicly funded. Funding has been already identified as a main challenge for the conduct IICS and especially for clinical trials (IICTs, IICS where a medical intervention is directly tested). Main barriers to the conduct of multinational IICTs with public funding include: Limitations of budget and duration of the eligibility of costs Lack of flexibility to move funds transnationally Tendering rules Complexity in the reporting of the eligible costs to funders We describe why there is a need to support multinational IICS, what should be their objectives and what are the current funding mechanisms in Europe. Strategies for funding multinational IICS should evolve to mitigate identified barriers, thus facilitating research that can provide answers to highly relevant questions in healthcare which are less likely to be answered by studies funded by the pharmaceutical and medical device industry. [ABSTRACT FROM AUTHOR]

With the development of supercharging technology, charging stations will face supercharging piles and fast-charging piles coexisting for a long time. The traditional unified service fee pricing model will face the problem of slow-charging vehicles occupying supercharging piles, and the advantages of supercharging facilities cannot be fully utilized. Considering factors such as station revenue, station utilization rate, and user willingness, this paper constructs a differentiated pricing model for multi-power-level charging facilities based on capacity and electricity service fees. It reveals the impact of this pricing model on the economy and user satisfaction of charging stations. In addition, a multi-objective optimization model is constructed and solved by a multi-objective particle swarm method to determine the pricing strategy of different power levels that adapt to the actual situation. The results show that the differentiated pricing mechanism can increase the station revenue by about 10.74% and the station stack power utilization rate by about 7.14%, and user satisfaction is higher, which is better than the conventional pricing mechanism. Therefore, the proposed charging pricing strategy can provide a decision-making reference for charging station operation and planning. [ABSTRACT FROM AUTHOR]

This study aimed to analyze worldwide sales of new therapeutic agents and to estimate the time it takes for product sales to exceed industry-wide average drug development costs. Data obtained from company reports were analyzed to track worldwide sales of new medicines approved by the US Food and Drug Administration from 1995 to 2014. All sales figures were reported in 2019 US dollars. Kaplan-Meier curves were used to evaluate the time it took for discounted product sales to exceed the average costs associated with developing 1 new drug (accounting for the costs of failed trials), using published estimates of these costs. Based on data for 361 of 558 new therapeutic agents approved over the study period (median follow-up 13.2 years), mean sales revenue per product was $15.2 billion through the end of 2019; the median was $6.7 billion. These products jointly generated global sales of $5.5 trillion since approval. Revenues were highly skewed, with the 25 best selling products (7%, 25 of 361) accounting for 38% of this amount ($2.1 trillion of $5.5 trillion). Approximately 47% of products had discounted sales that exceeded the estimated industry-wide average costs of development within 5 years of approval, and 75% within 10 years. After attributing potential production, marketing, and other costs, these numbers dropped to 21% of products within 5 years of approval, and 46% within 10 years. Sales of new medicines approved from 1995 to 2014 were highly skewed, but many products had net discounted sales that exceeded the industry-wide average costs of development within 10 years of approval. An understanding of how sales revenues accrue in the years after initial approval, alongside data on business costs, can inform discussions about how to incentivize private investment in innovation while ensuring affordable prices for patients and the healthcare system. • Little is known about how much drug companies earn in sales revenues for new medicines and how long it takes them to recover the costs of research and development. • Based on data for 361 of 558 new therapeutic agents approved by the US Food and Drug Administration from 1995 to 2014, median worldwide sales per product was $6.7 billion through 2019 (median follow-up 13.2 years). Approximately 2 in 10 drugs had net discounted sales that exceeded the industry-wide average cost of development within 5 years of approval, and 1 in 2 within 10 years of approval (after accounting for production, marketing, and other costs). • Companies generated large revenues on sales of new drugs approved from 1995 to 2014, although sales were highly skewed. An understanding of the revenues earned by pharmaceutical companies on brand-name drugs, alongside data on business costs, can inform discussions about how to incentivize private investment in innovation while ensuring affordable prices for patients and the healthcare system. [ABSTRACT FROM AUTHOR]

Even though Hotel mini bars is an excellent service and product delivery channel during the guest stay, typical selections of varieties and displays have been used without innovative ideas. This study argues that Mini Bars in the hotel can be capitalized to share the Hotel's Corporate Social Responsibility vision and enhance customer perception toward the hotel brands with revenue increase. The current study adopts Discrete Choice Modeling to investigate the best choice attributes and levels of hotel mini bar. The results address how the hotel and local industry can co-create value for the hotel, local businesses, and guests. [ABSTRACT FROM AUTHOR]

This study looks into how the COVID-19 pandemic has affected the revenue of Indonesia's West Sumatra Province's micro and small industries (MSI). Ordinary least square analysis is used in the study methodology taking into account classical assumption tests for heteroscedasticity and multicollinearity. This research data is in the form of panel data from 2018 to 2020 covering 19 regencies and cities. The results show that the COVID-19 pandemic has had a negative and considerable effect on West Sumatra Province's revenue from MSI. The COVID-19 pandemic has impacted the decline in revenue for MSI. The government should actively provide subsidies and assistance to MSI in West Sumatra Province particularly during COVID-19. Implementing various supportive regulations can further ensure the sustainability of MSI. [ABSTRACT FROM AUTHOR]

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The implementation of promotional pricing strategies constitutes a key component within the realm of retail revenue management. Nonetheless, the accurate prediction of sales in the presence of price discounts proves challenging due to the influence of various factors that contribute to demand uncertainty and high fluctuations. This study aims to find the most suitable prediction models for retail product unit sales while comprehensively accounting for the complex impacts of contributing factors. The dataset, sourced from a case study of a retail company, spans the temporal interval from January 2020 to December 2022. The predictive models, encompassing linear regression, random forest, XGBoost, artificial neural networks, and hybrid machine-learning models, are systematically developed. Then, the identification of the most suitable model is facilitated through the computation and comparative analysis of the Mean Absolute Percentage Error, with due consideration given to the weighting by the respective product's revenue, thereby offering a comprehensive assessment of overall performance. Additionally, different types of feature selection are experimented. Factors used in machine learning models are either using all the independent variables or using significant factors from the stepwise method, and either considering or not considering exogenous factors of other products in the same cluster grouped by category, subcategory, or K-means method. The result shows that the series hybrid model of random forest and XGBoost outperformed others. Considering factors affecting sales, it is found that the promotion period factor was the most important, followed by discount percentage and price factors. This research provides analytics framework for sales prediction for retails using promotional pricing as a key demand driver. [ABSTRACT FROM AUTHOR]

Using total revenue, previous research finds college basketball players generate millions of dollars in marginal revenue product (MRP). We are skeptical of using total revenue data. Instead, we use total variable revenue since using fixed revenues can over‐estimate a team's marginal revenue and therefore a player's MRP. Comparing MRP to the players average grant‐in‐aid, we find that for public Division I universities, a little over one‐quarter of men's basketball players are exploited and a little over one‐tenth of women's basketball players are exploited. [ABSTRACT FROM AUTHOR]

The 2010 Patient Protection and Affordable Care Act (ACA) linked acute care hospital reimbursements to quality-of-care measures. While the impact of healthcare quality on service provision is well-documented, the effects of 30-day readmissions on hospital financial performance are less understood. This study examines the relationship between 30-day readmission rates and financial performance in U.S. acute care hospitals from 2010 to 2018 using four financial metrics: operating margin, operating revenue, operating cost, and total margin. Data were sourced from the American Hospital Association (AHA) Annual Survey, Centers for Medicare and Medicaid Services (CMS), Area Health Resource Files (AHRF), and CMS cost reports. Univariate analysis of hospital characteristics was followed by an unbalanced panel regression with hospital and year-fixed effects. Inflation adjustments and controls for HRRP, CMI, managed care penetration, payer mix, physician supply, RN and MD staffing, occupancy, and mortality rates were applied. Increased readmission scores for AMI correlated with higher adjusted operating revenues per patient day (β = $26.86, p ≤.001), but no significant changes in adjusted operating cost, operating margin, or total margin. Following HRRP implementation, adjusted operating revenue decreased for AMI (β = $425.21, p ≤.019), HF (β = $229.41, p ≤.023), and PN (β = $229.41, p ≤.023). HF readmission scores marginally increased the adjusted operating margin (β = $0.0002, p ≤.064) with no significant impact on other financial metrics. Pneumonia readmission rates marginally increased the adjusted operating margin (β = $0.0002, p ≤.064) without significantly affecting other financial measures. The study's findings highlight the potential financial benefits of reducing readmissions for hospitals. However, it also underscores the importance of developing and implementing broader quality metrics that can provide a more comprehensive evaluation of hospital performance, thereby enhancing the audience's understanding of the need for a comprehensive evaluation of hospital performance. [ABSTRACT FROM AUTHOR]

Duck hatchery waste is an alternative feed ingredient for protein sources in poultry. This study aimed to determine the effect of duck hatchery waste supplementation on growth performance, and income over feed cost of hybrid ducks. A total of 120-day-old male hybrid ducks (body weight: 61.4±4.9g) were randomly divided into three treatments (4 replicates per treatment, 10 ducks per replicate). At 0-14 days of age, ducks were fed the same complete feed in all treatments. After 14 days of age, ducks were fed an experimental diet until 35 days of age. The treatment feed consists of a basal diet (P0), basal diet with 8% hatchery waste (P1), and basal diet with 16% hatchery waste (P2). Supplementation of 8% and 16% duck hatchery waste increased accumulated feed consumption and body weight gain of hybrid ducks on day 35 (P<0.05). However, feeding duck hatchery waste did not affect the feed conversion ratio of hybrid ducks on week 5. In contrast, supplementation of duck hatchery waste decreased the FCR of hybrid ducks at weeks 3 and 4. Furthermore, the inclusion of duck hatchery waste in the duck diet increased revenue generation from duck sales and increased the IOFC value. In conclusion, supplementation of duck hatchery waste can increase feed intake and body weight gain, duck sales and IOFC value of hybrid ducks. [ABSTRACT FROM AUTHOR]

Using a representative survey of Dutch entrepreneurs and self-employed individuals, (i) we measure their subjective financial knowledge and the extent to which they ask for advice when managing their companies, and (ii) we examine whether subjective financial knowledge and the demand for advice are related to the firm economic performance. We find that the respondents feel more comfortable with accounting subjects than they do with strategic ones, of which they feel that they know the least. Entrepreneurs with a greater extent of financial knowledge are more likely to report a higher gross margin and higher revenue growth for their firm. These entrepreneurs are also less likely to seek advice and to delegate financial decisions. Seeking professional advice does not increase the likelihood of an entrepreneur having better performance. Our results suggest that entrepreneurs' degree of financial knowledge is related to the success of their businesses, while seeking advice is not significantly correlated with better firm performance. [ABSTRACT FROM AUTHOR]

State and local government decisions about how school funding is raised and allocated have profound impacts on American public education, and in recent years, experts have documented large increases in one type of spending in particular: public pensions. Because most data on school district pension expenditures are at the state level, it has so far been difficult to assess what changes local school districts have made in response. In this paper, I analyze a new dataset of the annual pension expenditures of approximately 200 unified school districts across the United States from 2005 to 2016. Consistent with findings in the literature, I find that pension expenditures rose in real terms in most of them, but also that there has been significant variation in that growth. Moreover, in a descriptive analysis, I find that larger within-district pension expenditure growth is associated with (1) greater revenue growth in the subsequent year and (2) reductions in school district employment, mainly through reductions in the number of non-teaching staff. Finally, there is evidence that districts' responses to rising pension expenditures may depend on state political institutions, in particular whether the states have mandatory collective bargaining for teachers. [ABSTRACT FROM AUTHOR]

We study the effects of new shopping centre developments on the performance of 7041 retail and hospitality firms located in the suburbs of Stockholm, Gothenburg, and Malmö. In particular, we analyse to what extent these effects vary with respect to the distance to, and characteristics of, these newly established centres. Exploiting data covering a 17-year period (2000–2016) in a fixed-effects panel regression framework, we find that the establishment of new neighbourhood centres is associated with an average increase in revenues and employment for retail incumbents by + 1.80% and + 1.20%, respectively, for each 100-m reduction in distance to the respective centre. Similarly, the introduction of large regional centres is associated with an increase in the revenues and employment of hospitality firms by + 1.40% and + 1.20%, respectively, for every 100-m decrease in proximity to the new shopping centre. Retail firms are affected by regional centres only in terms of their revenues, which increase by + 0.70% for each 100-m decrease in distance. Our results indicate a diminishing impact of both regional and neighbourhood centres with increased distance, suggesting a broader geographical reach for the effects of regional centres. [ABSTRACT FROM AUTHOR]