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Revenue management (RM) is a significant technique to improve revenue with limited resources. With the macro environment of dramatically increasing transit capacity and rapid railway transport development in China, it is necessary to involve the theory of RM into the operation and decision of railway passenger transport.

This paper proposes the theory and framework of generalized RM of railway passenger transport (RMRPT), and the thoughts and methods of the main techniques in RMRPT, involving demand forecasting, line planning, inventory control, pricing strategies and information systems, are all studied and elaborated. The involved methods and techniques provide a sequential process to help with the decision-making for each stage of RMRPT. The corresponding techniques are integrated into the information system to support practical businesses in railway passenger transport.

The combination of the whole techniques devotes to railway benefit improvement and transit resource utilization and has been applied into the practical operation and organization of railway passenger transport.

The development of RMRPT would provide theoretical and technical support for the improvement of service quality as well as railway benefits and efficiency.

As a disruptive technology, blockchain technology brings new opportunities and challenges to operations management. We aim to examine the influences of blockchain cooperation project announcements (BCPAs) on firms’ stock market reactions in an emerging market. From 2016 to 2021, a total of 113 BCPAs of listed firms from the Chinese A-share market are selected as samples.

This study is based on the loose coupling theory and uses the event study method and probit regression analysis.

We find BCPAs positively affect the firm’s stock price on the day they are released. Compared with vertical BCPAs in a supply chain, horizontal BCPAs exert a more positive market reaction. Moreover, a BCPA with a partner within a shorter geographical distance exerts a more positive influence on market reaction. Contrary to the intuition of the decentralized blockchain feature that one-to-many cooperation leads to better benefits, one-to-one BCPAs exert a more positive effect on market reaction than one-to-many BCPAs. We further find that (1) industry type has a certain impact on cooperation mode selection, and (2) manufacturing firms are more inclined to choose one-to-one cooperation than those in service industry.

We focus on the impact of blockchain cooperative announcements and additionally use the probit regression models to analyze the influencing factors of cooperation mode selection and find the critical role of the industry type, which complements the existing empirical research on blockchain announcements and is conducive to provide decision-making reference for managers.

The present study aims to identify how firms positioned their corporate reputation (i.e. impressiveness vs respectability) in their initial public offering (IPO) communication based on the impression formation model. Further, the study examined whether this presentation of corporate reputation was related to IPO success (i.e. stock price and volume of trading).

The present study analyzed 248 IPO prospectuses that were submitted to the major US stock markets. Specifically, various substantive and symbolic information and cues in IPO prospectuses were content analyzed.

The results suggest that bigger (in terms of revenue) IPO companies featured more “impressiveness” in their IPO prospectus, leading to greater IPO success. Bigger (in terms of both revenue and number of employees) IPO companies featured more “respectability” impressions in the IPO prospectus, although they did not achieve direct IPO success on the first day of IPO. Different types of industry used different information cues to feature “impressiveness” and/or “respectability,” suggesting that different types of firms view different cues to be important to IPO communication.

The results also suggest some practical guidelines for the strategic use of contents, tables and illustrations. Using more charts, tables and illustrations in IPO prospectus summaries was associated with a higher volume of trading on the first day. The more illustrations included in the IPO prospectus summaries, the less investors were willing to pay for initial stock prices.

IPO communication is a generally understudied area in corporate communication and strategic communication scholarship. The results should help to explain which communicative aspects and PR strategies effectively manage the firm’s impression to maximize the chances of an IPO success as well as initially build the financial reputation of a company. By doing so, the findings contribute to the broader advancement of financial communication within the strategic communications domain.

Digital platforms that offer on-demand gig work, while providing work opportunities in the economy, have raised social and economic concerns. Though extensive research on regulation of the gig economy exists, the effect of economic regulations on the welfare of the workers is not well understood. In this work, this paper aims to specifically study the effect of minimum wage and leisure regulations on the unemployment rate and offered wages. This paper also analyses the effect of up-skilling of the workers on unemployment and wages.

This paper builds an agent-based model of the labour market with heterogeneous workers and online platform firms that interact to match supply and demand. This paper also interviewed online workers in the two under-studied markets in online beauty and house maintenance services in India and included salient observations in to the model. This paper further validates the model findings with the interview observations.

Extensive simulations of the model indicate that the regulator's intervention on minimum wage and leisure reduces unemployment and offers better wages/leisure in the short term. However, these cannot be sustained unless the workers upgrade their skills, thereby improving their value to the employers. This paper also corroborates the authors’ interview observations on platforms deviating on stated worker contracts by simulating the same in the model. This paper finds that when platforms deviate on their stated incentive schemes, the unemployment rate tends to increase. This paper also finds that the emergence of online platforms in an erstwhile off-line market decreases the average unemployment rate with a moderate increase in the offered wage and leisure.

In this work, the focus has been to determine the worker-platform dyadic relationship. However, this is affected by consumer-related attributes such as ratings and associated reputation systems to promote trust between different stakeholders. Examining such a triadic relationship between consumers, platform and workers is required to comprehensively address the challenges of online gig economy.

Skilling and training are critical for worker mobility across tasks and jobs, especially in the gig economy. Gig workers, in general, seek to improve their skill level through self- or platform-enabled training programmes. The workers are able to generate more revenue through the new skills and hence can improve their reservation wage as well. This in turn increases average offered wages and reduces the overall unemployment in the sector. Despite attempts to classify gig workers as formal workers by labour laws across countries, there is resistance from online platforms. This is due to increased liability and responsibility that the platforms have to incur that possible increase their costs and expenses. This study shows that regulations, such as minimum leisure or minimum wage, increase the average wage or leisure in the market and increase unemployment. However, this might be a short-term phenomenon. In the long term, the gig workers benefit by enhancing their skills to not only stay employed but also bargain for better wages and leisure. The governments can play a larger role by facilitating upskilling programmes for the gig workers.

An extensive literature survey indicates that while most of the work on gig economy regulation emphasises the social and legal aspects, this work is unique in modeling the techno-economics of gig work. Further, while most of the economic research on gig work, focuses on consumers, this work focuses on the under-researched area of worker welfare. This paper also validates the model results with findings from the interviews with gig workers.

Supply chain revamping (SCR) is an important strategy for firms to improve their supply chain operations in a rapidly changing environment. The purpose of this study is to shed light on the impact of SCR on shareholder value.

Based on Signaling Theory and 184 SCR announcements published by US-listed firms from 2013 to 2018, this study employs event study methodology and empirically examines three issues: Antecedents of SCRs; Primary purposes and actions of SCRs; In addition to the impact of SCRs on shareholder value using stock returns, we also examined the factors that can influence the extent of stock returns.

Firstly, our results indicate that SCRs are primarily driven by firms’ poor prior performance, CEO turnover and external control threats (ECTs). Secondly, the stock market favors SCRs aiming to meet customer needs and those accomplished through network remodel. However, the market reacts negatively to SCRs aiming at cutting costs, improving poor performance, and those implemented through network trim. Finally, the cross-sectional analysis indicates that shareholders prefer firms operating in more competitive or faster-growing industries and those adopting an expansionist strategy than those adopting a streamlining strategy.

Our study provides managers with valuable insights into when firms can benefit from initiating SCRs not only by examining the purposes and actions of SCRs but also by examining the industry- and strategy-specific moderators. Our study illuminates the conditions under which SCR will positively affect shareholder value. Additionally, this study contributes to the existing literature by deepening the understanding of the impact of supply chain decisions on firm performance and identifying the marginal conditions under which the stock market will react positively to SCR announcements.

This study investigates whether the underrepresentation of women in executive-level roles within the supply chain management (SCM) field is justified or the result of gender injustices. The analysis examines if there is a gender compensation gap within executive-level SCM roles and whether performance differences or other observable factors explain disparities.

Publicly reported executive compensation and financial data are merged to empirically test if gender differences exist and investigate whether the underrepresentation of women in executive-level SCM roles is unjust.

Women occupy only 6.29% of the positions in the sample of 447 SCM executives. Unlike prior studies, we find that women executives receive higher compensation. The analysis does not identify observable factors explaining the limited inclusion of women in top-level roles, suggesting that gender injustices are prevalent in SCM.

This study only considers observable factors and cannot conclusively determine if discrimination is occurring. The low level of inclusion of women in executive roles suggests that gender injustice is intrinsic within the SCM profession. These findings will hopefully motivate firms to undertake transformative actions that result in outcomes that advance gender equity, ultimately leading to social justice for female SCM executives.

The use of social justice and feminist theories, a focus on SCM roles, and an empirical methodology utilizing objective measures represents a novel approach to investigating gender discrimination in SCM organizations, complementing prior survey-based studies.

This study aims to investigate the daily performance of the proposed microgrid (MG) that comprises photovoltaic, wind turbines and is connected to the main grid. The load demand is a residential area that includes 20 houses.

The daily operational strategy of the proposed MG allows to vend and procure utterly between the main grid and MG. The smart metre of every consumer provides the supplier with the daily consumption pattern which is amended by demand side management (DSM). The daily operational cost (DOC) CO2 emission and other measures are utilized to evaluate the system performance. A grey wolf optimizer was employed to minimize DOC including the cost of procuring energy from the main grid, the emission cost and the revenue of sold energy to the main grid.

The obtained results of winter and summer days revealed that DSM significantly improved the system performance from the economic and environmental perspectives. With DSM, DOC on winter day was −26.93 ($/kWh) and on summer day, DOC was 10.59 ($/kWh). While without considering DSM, DOC on winter day was −25.42 ($/kWh) and on summer day DOC was 14.95 ($/kWh).

As opposed to previous research that predominantly addressed the long-term operation, the value of the proposed research is to investigate the short-term operation (24-hour) of MG that copes with vital contingencies associated with selling and procuring energy with the main grid considering the environmental cost. Outstandingly, the proposed research engaged the consumers by smart meters to apply demand-sideDSM, while the previous studies largely focused on supply side management.

This paper aims to investigate and formulate several business models (BM) for various energy communities (EC) members: prosumers, storage facilities, electric vehicle (EV) charging stations, aggregators and local markets.

One of the flexibility drivers is triggered by avoiding the cost and maximizing value that consists of delivering a service such as increasing generation or reducing consumption when it is valued most. The transition to greener economies led to the emergence of aggregators that aggregate bits of flexibility and handle the interest of their providers, e.g. small entities such as consumers, prosumers and other small service providers. On one hand, the research method consists of formulating six BM and implementing a BM that includes several consumers and an aggregator, namely, scheduling the household electricity consumption (downstream) and using flexibility to obtain revenue or avoid the cost. This is usually performed by reducing or shifting the consumption from peak to off-peak hours when the energy is cheaper. Thus, the role of aggregators in EC is significant as they intermediate small-scale energy threads and large entities' requirements, such as grid operators or retailers. On the other hand, in the proposed BM, the aggregators' strategy (upstream) will be to minimize the cost of electricity procurement using consumers’ flexibility. They set up markets to buy flexibility that is valued as long as their costs are reduced.

Interesting insights are revealed, such as when the flexibility price doubles, the deficit coverage increases from 62% to 91% and both parties, consumers and retailers obtain financial benefits from the local market.

One of the limitations of using the potential of flexibility is related to the high costs that are necessary to implement direct load control. Another issue is related to the data privacy aspects related to the breakdown of electricity consumption. Furthermore, data availability for scientific research is limited. However, this study expects that new BM for various EC members will emerge in the future largely depending on Information Communications and Technology developments.

An implementation of a local flexibility market (LFM) using 114 apartments with flexible loads is proposed, demonstrating the gains obtained from trading flexibility. For LFM simulation, this study considers exemplifying a BM using 114 apartments located in a multi-apartment building representing a small urban EC situated in the New England region in North America. Open data recorded in 2016 is provided by UMassTraceRepository.

As a novelty, six BM are proposed considering a bottom-up approach and including various EC members.

This study examines the impact of outcome uncertainty on the National Football League (NFL) secondary ticket market prices. As a demand-driven market, it is essential to comprehend how resellers respond to outcome uncertainty, one of the consumer demand factors in sports.

Using real-time ticket prices and money lines as a proxy of the probabilities of winning, this study employs a regression analysis and examines 33,554 price observations from the NFL’s secondary ticket market partner, StubHub.

The result shows a positive relationship between outcome uncertainty and secondary market ticket prices, indicating that resellers adjust the prices in response to the level of outcome uncertainty and put more value on games with greater uncertainty. This finding confirms the demand-driven nature of the secondary ticket market, as outcome uncertainty is one of the demand factors in sports.

This study links the uncertainty of outcome hypothesis with secondary ticket market pricing and fills a gap in the literature by providing an important perspective on games with uncertainty in the secondary ticket market. Outcome uncertainty has limited understanding in relation to secondary ticket market pricing despite its relationship with consumer demand. The positive relationship between outcome uncertainty and the ticket prices, grounded in real-time price data and win probability from sport betting markets, enhances our understanding of price determinations in the secondary ticket market.

This study aims to examine the timing of corporate disclosure in the context of Georgia, an emerging market where a recent reform of corporate financial transparency mandated about 80,000 private sector entities to publicly disclose their annual financial statements.

The main analysis covers more than 4,000 large, medium, small and micro private sector entities, for which the data is obtained from the Ministry of Finance of Georgia. This paper builds an empirical model of logit/probit regression, with industry fixed and random effects to investigate the drivers of the corporate disclosure timing.

Findings suggest that the mean reporting time lag is 279 days after the fiscal year-end, that is nine days after the statutory deadline. Almost one-third (30%) of the entities miss the nine-month statutory deadline, while the timely filers almost unexceptionally file immediately before the deadline. Multivariate tests reveal that voluntarily filing entities completed the process significantly faster than those mandated to do so; audited financial statements take more time to be filed, whereas those with unqualified audit opinion or audited by large/international audit firms are filed faster than their counterparts. The author concludes that despite the overall high filing rates, the timing of corporate disclosure is not (yet) efficiently enforced in practice (but is progressing over time), whereas regulatory incentives prevail over market incentives among the timely filers.

To the best of the author’s knowledge, this is the first study that explores corporate disclosure timing incentives in the context of Georgia. This study extends prior literature on the timing of financial information from an emerging country’s private sector perspective, with juxtaposed market and regulatory incentives.