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This paper studies the interactive valuation discourses of an online user community (transfermarkt.de) that seeks to determine market values for soccer players. Despite their seemingly casual nature, these values have featured in newspapers, transfer negotiations, academic research, and capital market communication – and have thus become reified.

The paper employs netnographic research methodology to collect and thematically analyze a wide range of user entries on the platform. These entries are studied using theoretical insights from the sociology of quantification and valuation.

The analysis reveals how values are constructed in constant interaction between value-proposing users and value-justifying “experts.” This dynamic form of relational valuation positions players relative to one another as well as to actual transactions on the transfer market. In the absence of authoritative guidelines, it is this possibility and affordance for interaction that enacts a coherent valuation regime. The paper further reveals the platform's response to a disruptive event, which risked bringing the user-expert dynamics to a halt, requiring intervention from the platform to repair its valuation frame.

The paper responds to increased scholarly interests in the valuation of professional athletes. It contributes to the extant literature on valuation, first, by analyzing the dynamic valuation work that feeds into the social construction of values and, second, by studying platform participation and user interaction in a socially engineered online space.

This article explores the value creation process from player sales in football to understand if the related capital gains correspond to significant increases in the stock value of selling companies. In addition, it aims to detect any potential drivers for higher (or slower) abnormal stock returns.

The authors analyze all the capital gains of the Italian and Portuguese listed football companies (the only ones for which, based on their annual reports, it was possible to trace the net book value for each player sold and, consequently, if any, the related capital gain) from 2012 to 2020 and use event study analysis to calculate the abnormal returns of the football companies' stocks. Moreover, the authors use a multiple linear regression model to identify the factors affecting investors' reactions and value creation process intensity.

The results show that, on average, the capital gains from player transfers in football are positive income components and produce statistically significant higher abnormal returns. In addition, the authors identified some relevant drivers related to their intensity which could guide the choices of corporate executives regarding future disposals of the multi-year performance rights of players in the roster.

This study considers only Italian and Portuguese football listed companies. It would be helpful to consider some of the companies from other countries which are also outstanding from the sports perspective, but, in practice, it was not possible due to the impossibility to trace the net book value of the single footballers sold in those clubs' public financial disclosure.

The value relevance of the capital gains from player trading activities should increase their importance, creating cascade effects on several activities generating value for football clubs (youth sector management, player scouting, technical improvement of the players). In addition, financial data show that the capital gains from player transfers are a basic income of European football clubs nowadays. Their executives consider these operations recurrent and continually search for more valuable transfers. Hence, it is reasonable to think that they (will) choose the players to sell considering both sports and financial aspects.

To the best of the authors' knowledge, this is the first study exploring the effects of capital gains from player trading activities on professional football clubs' stock value. The results obtained are even more relevant if one considers the importance these income components have in the profit formula of professional football clubs nowadays, also because of the negative repercussions caused by the recent COVID-19 pandemic.

This study aims to examine farmers' decision to use smartphone agricultural applications (SAAs) and how SAAs adoption impact their land transfer behaviors in terms of the current land transfer-in area (LTA) and the future willingness to renew land transfer-in after it expires (WTR).

This study provides empirical evidence on the relationship between farmers' use of SAAs and land transfer choice, using a field survey data of 752 rural farm households in 2020 from Sichuan province of China. The endogenous switching models are employed to address potential self-selection bias associated with voluntary SAAs use and to quantitatively examine the impacts of SAAs use on land transfer choice.

The empirical results reveal that SAAs significantly improves the probability of transfer-in of more land by 39.10%. We find SAAs use has heterogeneous impacts on land transfer-in choice in the groups of agricultural technology, extension service, marketing and credit. Besides, we also find that SAAs use exerts highly positive and significant impact on farmers with less land area transfer-in. Moreover, SAAs can increase the probability of farmers' willingness to renew the land transfer-in by 30%.

To the best of our knowledge, this study is the first to explore the quantitative relationship between the use of SAAs and farm households' land transfer choice. The findings of this work can provide policy-related insights to help government promote the development of digital applications in the agricultural sector.

The results of this study have significant policy implications for charting a new course toward enhancing agricultural productivity among Chinese farmers.

By establishing a rural household decision-making model based on the transfer market of farmland operation rights, this paper systematically analyzes the effects of land transfer-in and land transfer-out on the productivity (per labor income) of rural households. The authors conducted basic regression analysis and robustness tests using propensity score-matching and proxy variable approaches based on the micro survey data from rural households in 30 counties in 21 provinces/municipalities/autonomous regions in 2013.

After the completion of land transfer, the total productivity of rural households transferring in lands will increase with an increase in the agricultural productivity; the total productivity of rural households transferring out land will increase due to a rise in non-agricultural productivity and the absolute total productivity of rural households not involved in land transfer will remain unchanged.

Unlike previous literature, this paper discusses the impacts of land transfer-in and transfer-out on total productivity, agricultural productivity and non-agricultural productivity among various rural households (i.e. those transferring in land, transferring out land or which are self-sufficient).

Farmland transfer choice is strongly associated with the livelihood strategies of rural households. The 2014 Three Property Rights Separation (TPRS) reform has legalized farmland transfer practices in rural China, hence stimulating the farmland transfer market at the national scale. This paper aims to determine the extent to which rural family livelihood strategies are influenced by their participation decision in farmland transfer practices. Further, the authors examined the effectiveness of the TPRS reform on the impact of farmland transfer participation on rural household livelihood strategy choices.

Based on the sustainable livelihood approach (SLA) using data from a national rural household survey, the authors employ the logit model and the propensity score matching (PSM) method to estimate the impact of household farmland transfer participation. Its interaction effects with household livelihood capital on their livelihood strategy choices and diversification level are also investigated. The difference-in-difference (DID) model is employed to assess the effectiveness of the TPRS reform.

The results indicate that the participation in transferred-out farmland could improve rural households' non-agricultural livelihood strategies. While the participation in transferred-in farmland could improve the probability of rural families' engaging in pure-agricultural (PA) or agricultural-dependent (AD) livelihood strategies, the TPRS reform can attract specialized farmers to increase their farm size through the market solutions and encourage small farmers to leave their farmland to engage in more off-farm work.

This study contributes to the literature on farmers' livelihood by exploring the role of farmland transfer decision and the effectiveness of 2014 TPRS reform through the SLA approach.

This research aimed to measure the influence of resource dependency (trading and/or shareholder's dependencies) squad age structure by building archetypes to identify strategic dominant schemes.

Based on the Ligue 1 football clubs from the 2009/2010 season to the 2018/2019 data, the authors use the k-means classification to build archetypes of resource dependency and squad structure variables. The influence of resource dependency on squad structure is then analysed through a table of contingency.

Firstly, the authors identify archetypes of resource dependency with some clubs that are dependent on the transfer market and others that do not count on sales to balance their account. Secondly, they provide different archetypes of squad structure choices. The contingency between those archetypes allows to identify three main strategic schemes (avoidance, shaping and adaptation).

The research tests an original relationship between resource dependency of clubs and their human resource strategy to respond to it. This paper can help to provide detailed profiles for big clubs looking for affiliate clubs to know which clubs have efficient academy or player development capacities.

The purpose of this paper is to develop a commercialization model based on gaining economic benefits through the transfer of technological capabilities in the oil and gas industry. Since commercialization models are mostly based on the implement of technology to produce and sell new products, this study focuses on developing a specific independent technology commercialization model.

The method of this research is qualitative based on the grounded theory. For this purpose, general variables with content analysis were extracted by reviewing documents (Literature review) and then for identifying special components, interviewing experts in the Iranian oil and gas industry. Participations were selected using snowball sampling for semistructured interviews.

The findings of this research were extracted based on grounded theory with data analysis in MAXQDA software. In this research, first, 210 open codes were identified based on qualitative content analysis of relevant documents and results of interviews with experts. Then the classification of open codes was done, and 46 subcategories (variables) were determined in the commercialization model. Finally, 46 subcategories were classified into 10 categories as axial codes in grounded theory as components of the commercialization model.

The results of this research have led to the creation of new practical and theoretical implications. In this research, a new perspective of commercialization with the aim of transferring technology and obtaining its economic benefits for oil and gas industry companies was discussed. Also, based on the practical implications explained in this research, policymakers can use the suggested model to effectively implement independent technology commercialization to acquire economic benefits.

This study is purely original and the outcome of the research conducted by the authors. The research findings are the outcome of in-depth study on technology commercialization in the Iranian oil and gas industry.

This study aims to understand the role of drivers, underlying challenges and, consequently, the implications of the reverse knowledge transfer (RKT) process for the multinational enterprises (MNE)s.

A dyadic qualitative research design was used with a cross-country design covering perspectives from both the headquarters and subsidiaries from the USA, Denmark, Pakistan, India and Bangladesh. In-depth interviews were conducted with managers in multiple sectors such as information technology, telecommunications, project management and engineering.

The study reveals the constraints and drivers of the RKT process, and furthermore elaborates on the implications for MNEs. RKT can lead to the development of new processes, subsidiary independence and intra-organizational knowledge transfer. Besides, it can entail challenges such as position insecurity for subsidiaries and a blurring of the MNE market vision. The findings demonstrate several implications for the MNEs.

The study highlights the direct implications of RKT for the multinational enterprises. The findings serve as a practical guide for global managers seeking to improve their competitive edge.

The study presents a framework of the RKT process from emerging market subsidiaries to parent companies, that demonstrates the role of drivers, underlying challenges and implications of the RKT process for the MNEs.

This paper researches a bidirectional volatility transmission effect between stocks and exchange rate markets in the six East European and Eurasian countries.

Research process involves creation of transitory and permanent volatilities via optimal component generalized autoregressive heteroscedasticity (CGARCH) model, while these volatilities are subsequently embedded in Markov switching model.

This study’s results indicate that bidirectional volatility transmission exists between the markets in the selected countries, whereas the effect from exchange rate to stocks is stronger than the other way around in both short-term and long-term. In particular, the authors find that long-term spillover effect from exchange rate to stocks is stronger than the short-term counterpart in all countries, which could suggest that flow-oriented model better explains the nexus between the markets than portfolio-balance approach. On the other hand, short-term volatility transfer from stock to exchange rate is stronger than its long-term equivalent.

This suggests that portfolio-balance theory also has a role in explaining the transmission effect from stock to exchange rate market, but a decisive fact is from which direction spillover effect is observed.

This paper is the first one that analyses the volatility nexus between stocks and exchange rate in short and long term in the four East European and two Eurasian countries.