Search results

This paper aims to demonstrate that Facebook likes affect outcomes in nonprofit settings. Specifically, Facebook likes influence affinity to nonprofits, which, in turn, affects fundraising outcomes.

The authors report three studies that establish that relationship. To examine social contagion, Study 1 – an auction field study – relies on selling artwork created by underprivileged youth. To isolate signaling, Study 2 manipulates the number of total Facebook likes on a page. To isolate commitment escalation, Study 3 manipulates whether a participant clicks a Facebook like.

The results show that Facebook likes increase willingness to contribute in nonprofit settings and that the process goes through affinity, as well as through Facebook impressions and bidding intensity. The total number of Facebook likes has a direct signaling effect and an indirect social contagion effect.

The effectiveness of the proposed mechanisms is limited to nonprofit settings and only applies to short-term effects.

Facebook likes serve as both a quality signal and a commitment mechanism. The magnitude of commitment escalation is larger, and the relationship is moderated by familiarity with the organization. Managers should target Facebook likes at those less familiar with the organization and should prioritize getting a potential donor to leave a like as a step leading to donation, in essence mapping a donor journey from prospective to active, where Facebook likes play an essential role in the journey. In a charity auction setting, the donor journey involves an additional step of bidder intensity.

The approach the authors study is shown effective in nonprofit settings but does not appear to extend to corporate social responsibility more broadly.

To the best of the authors’ knowledge, this study is the first investigation to map Facebook likes to a seller’s journey through signals and commitment, as well as the only investigation to map Facebook likes to charity auctions and show the effectiveness of this in the field.

The present study aims to provide a roadmap for meeting the carbon-free, green energy production target within the stipulated period while also considering climate targets through a sustainable auctioning scheme.

The research outlines the opportunity to design auctions based on qualitative research, the impact of auctions on energy costs and thus the feasibility of suggested auctioning schemes based on country-specific empirical evidence and benefits.

The conclusions show that this may result in various advantages for emerging economies relating to technology-neutral site-specific auctions if designed according to state-specific socio-economic conditions.

The planned addition to the state-of-the-art in the renewable energy (RE) field of this paper is that it intends to bridge the gap between theory and practice. The analysis has concepts for research, practice and/or community. Thus, it can serve as a primary source of literature reference for those willing to learn more about the aspects of cost related to RE.

This paper gives a model of collusion formation and a method of measuring the degree of it among the traders/bidders in the agricultural commodity markets in India. The important assumption is that the bidding is repetitive with a set of common bidders. The theory has been derived based on the behavior of the wholesale market of agricultural commodities in India. The paper is based on full information in the collusion formation. The paper first derives the theoretical structure of the bidders' behavior and thereafter derives a measure of collusion formation with the help of real-life data.

The paper used the standard theory of optimization and the theory of auction and probability statistics.

This is a complete information model of cartel formation. The bidding is repetitive and continues forever in discrete time. Hence bidders behavior is observable. Using the proposed method, if the APMC measures for each market and publishes on a periodic basis, say weekly basis, then it will be easier to break the collusion in the market where relative collision is present. For example, if a farmer has three options to sell in three different markets, then the published data would help them to select the market where the degree of collusion is relatively lower. Moreover, the undesirable loss can be avoided based on the right choice of market. As a result, transaction costs will be optima.

The paper first derives the theoretical structure of the bidders' behavior and thereafter derives a measure of collusion formation with the help of real-life data.

The purpose of this study is to determine whether the fine wine market is efficient between homogeneous lots and heterogeneous lots.

Auction price data for homogeneous (or solid) lots of fine wines was analyzed to create price prediction models. Those models were used to predict the expected auction price for the bottles within heterogeneous lots. Lastly, models were created to explain and predict the differences between expected and realized prices for heterogenous wine lots.

The results show that large inefficiencies exist. The more complex and expensive the heterogeneous lot, the greater the discount relative to what would have been realized if the bottles had been sold individually. This discount can exceed 50% of the expected auction price.

Heterogeneous lots may arise as a practical requirement from the auction house. Restaurant buyers probably have little interest in such lots because of the inclusion of wines the restaurant will be unable to sell. Collectors may be uniquely positioned to benefit from this price discount.

These results are unique in the literature, because the price dynamics of heterogeneous (or mixed) lots of fine wines have not previously been studied.

Social media networks make their services freely available to all users. Users pay for the service received with the time and attention taken by the advertisements. This chapter argues that social media platforms are a unique form of monopoly driven by “the more the merrier” effect (i.e., network effects) in users' consumption. These monopolies exercise market power, not by charging higher prices to users but by “tying” larger amounts of advertising to their content. Traditional antitrust instruments designed to address excessive pricing and reduced output by monopolies need to be reframed to tame the attention economy problems in the social media industry. This chapter discusses five antitrust instruments grouped in three categories: structural, behavioral, and market-based remedies. Market-based solutions are the least explored in the literature, despite being the most promising instruments to lower the attention costs imposed on users, while preserving the economies of scope in production and the network effects in consumption, and possibly maintaining free access to social media, as we know it today.

The paper proposes a research method to verify the perception bias of consumers on the freshness preservation effects of vacuum packaging (VP) and modified atmosphere packaging (MAP) chilled pork packages, the influence of “sensory experience” on correcting consumers' perception bias of packaging performance and willingness-to-pay (WTP) enhancement channels.

Using data from 458 and 188 participants who completed the contingent valuation method (CVM) and auction experiment, respectively, the study aimed to uncover consumers' packing quality perception bias and WTP, and investigated the societal factors that contribute to variations in WTP.

The CVM experiment revealed that although consumers' high perception bias rate toward MAP to maintain freshness, as compared to lab test results, came along with low WTP premium to cost rate with sensory experience in the auction experiment, the proportion of consumers with quality perception bias decreased from 49.85% to 34.46%, while the WTP premium to cost rate for MAP increased largely by 36.7%. Perceptive embedding has a positive effect on chilled pork packaging WTP, while normative embedding decreases WTP.

The findings emphasize the need of public policies to promote positive consumption attitudes, while whittling the negative consumption norms, to increase the WTP for packaged child pork and promote the chilled pork market formation.

Blockchain for energy trading is a trending research area in the current context. However, a noticeable gap exists in the review articles focussing on solar energy trading with blockchain technology. Thus, this study aims to systematically examine and synthesise the existing research on implementing blockchain technology in sustainable solar energy trading.

The study pursued a systematic literature review to achieve its aim. The data extraction process focussed on the Scopus and Web of Science (WoS) databases, yielding an initial set of 129 articles. Subsequent screening and removal of duplicates led to 87 articles for bibliometric analysis, utilising VOSviewer software to discern evolutionary progress in the field. Following the establishment of inclusion and exclusion criteria, a manual content analysis was conducted on a subset of 19 articles.

The results indicated a rising interest in publications on solar energy trading with blockchain technology. Some studies are exploring the integration of new technologies like machine learning and artificial intelligence in this domain. However, challenges and limitations were identified, such as the absence of real-world solar energy trading projects.

This study offers a distinctive approach by integrating bibliometric and manual content analyses, a methodology seldom explored. It provides valuable recommendations for academia and industry, influencing future research and industry practices. Insights include integrating blockchain into solar energy trading and addressing knowledge gaps. These findings advance societal goals, such as transitioning to renewable energy sources (RES) and mitigating carbon emissions, fostering a sustainable future.

This study aims to propose an efficient dual-robot task collaboration strategy to address the issue of low work efficiency and inability to meet the production needs of a single robot during construction operations.

A hybrid task allocation method based on integer programming and auction algorithms, with the aim of achieving a balanced workload between two robots has been proposed. In addition, while ensuring reasonable workload allocation between the two robots, an improved dual ant colony algorithm was used to solve the dual traveling salesman problem, and the global path planning of the two robots was determined, resulting in an efficient and collision-free path for the dual robots to operate. Meanwhile, an improved fast Random tree rapidly-exploring random tree algorithm is introduced as a local obstacle avoidance strategy.

The proposed method combines randomization and iteration techniques to achieve an efficient task allocation strategy for two robots, ensuring the relative optimal global path of the two robots in cooperation and solving complex local obstacle avoidance problems.

This method is applied to the scene of steel bar tying in construction work, with the workload allocation and collaborative work between two robots as evaluation indicators. The experimental results show that this method can efficiently complete the steel bar banding operation, effectively reduce the interference between the two robots and minimize the interference of obstacles in the environment.

This study aims to solve optimal pricing and power bidding strategy problem for integrated combined heat and power (CHP) system by using a modified heuristic optimization algorithm.

In electricity markets, generation companies compete according to their bidding parameters; therefore, optimal pricing and bidding strategy are solved. Recently, CHP units are significantly operated by generation companies to meet power and heat, simultaneously.

For validation, it is shown that profit is improved by 0.04%–48.02% for single and 0.02%–31.30% for double-sided auctions. As heat price curve is extracted, the simulation results show that when CHP system is integrated with other units results in profit increase and emission decrease by 3.04%–3.18% and 2.23%–4.13%, respectively. Also, CHP units significantly affect bidding parameters.

The novelties are pricing and bidding strategy of integrated CHP system is solved; local heat selling is considered in pricing and bidding strategy problem and heat price curve is extracted; the effects of CHP utilization on bidding parameters are investigated; a modified heuristic and deterministic optimization algorithm is presented.