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This paper aims to identify specific challenges and opportunities when crafting literature reviews of qualitative accounting research. In addition, it offers potential remedies to frequent challenges when conducting such reviews.

This piece is based on recent methodological advice on conducting literature reviews and my own experience when conducting and publishing reviews that primarily cover qualitative accounting research.

The author chart three typical advantages and three typical use cases of literature reviews of qualitative accounting research, as well as the typical process steps and outputs of such reviews. Along with these process steps, The author identifies three overarching specific challenges when conducting such reviews and discusses potential remedies. Overall, this paper suggests that literature reviews of qualitative accounting research feature idiosyncratic challenges but offer specific opportunities at the same time.

To the best of the authors’ knowledge, this paper is among the first to offer advice on the specific challenges and opportunities when conducting literature reviews of qualitative accounting research.

The purpose of this study is to identify, characterize and assess supplier flexibility measurement practices in the order-to-delivery process.

The study involved a survey; participants were 224 purchasing managers at Swedish manufacturing companies that had more than 20 employees.

Scrutiny of the details of measurement practices revealed that most respondents actually do not specifically measure supplier flexibility. Instead they measure other measures like delivery reliability, conduct qualitative follow-ups, or cannot specify how supplier flexibility is measured. It was acknowledged that they measure different supplier flexibility aspects, and the applied measures were characterized, e.g. in terms of which flexibility dimension they represent.

Conceptual clarifications and adaptations to measuring supplier flexibility in the order-to-delivery process are provided. The identified measures can be a contribution in further developing literature on flexibility performance measurement.

Purchasing, logistics and supply chain managers in search of supplier flexibility performance measurement can find ways to measure and an extended flexibility vocabulary. This has the potential to improve flexibility in the supply chain.

Even though flexibility is claimed as being an important competitive advantage, few empirical studies and operationalized measures exist, particularly in the order-to-delivery process.

The objective of this paper is to examine the determinants of the Greek house market during the period 2006–2022 using not only economic variables but also behavioral variables, taking advantage of available information on the volume of Google searches. In order to quantify the behavioral variables, we implement a Python code using the Pytrends 4.9.2 library.

In our study, we assert that models relying solely on economic variables, such as GDP growth, mortgage interest rates and inflation, may lack precision compared to those that integrate behavioral indicators. Recognizing the importance of behavioral insights, we incorporate Google Trends data as a key behavioral indicator, aiming to enhance our understanding of market dynamics by capturing online interest in Greek real estate through searches related to house prices, sales and related topics. To quantify our behavioral indicators, we utilize a Python code leveraging Pytrends, enabling us to extract relevant queries for global and local searches. We employ the EGARCH(1,1) model on the Greek house price index, testing several macroeconomic variables alongside our Google Trends indexes to explain housing returns.

Our findings show that in some cases the relationship between economic variables, such as inflation and mortgage rates, and house prices is not always consistent with the theory because we should highlight the special conditions of the examined country. The country of our sample, Greece, presents the special case of a country with severe sovereign debt issues, which at the same time has the privilege to have a strong currency and the support and the obligations of being an EU/EMU member.

The results suggest that Google Trends can be a valuable tool for academics and practitioners in order to understand what drives house prices. However, further research should be carried out on this topic, for example, causality relationships, to gain deeper insight into the possibilities and limitations of using such tools in analyzing housing market trends.

This is the first paper, to the best of our knowledge, that examines the benefits of Google Trends in studying the Greek house market.

Twitter is the most widely used platform with an open network; hence, tourists often resort to Twitter to share their travel experiences, satisfaction/dissatisfaction and other opinions. This study is divided into two sections, first to provide a framework for understanding public sentiments through Twitter for tourism insights, second to provide real-time insights of three Indian heritage sites i.e., the Taj Mahal, Red Fort and Golden Temple by extracting 5,000 tweets each (n = 15,000) using Twitter API. Results are interpreted using NRC emotion lexicon and data visualisation using R.

This study attempts to understand the public sentiment on three globally acclaimed Indian heritage sites, i.e. the Taj Mahal, Red Fort and Golden temple using a step-by-step approach, hence proposing a framework using Twitter analytics. Extensive use of various packages of R programming from the libraries has been done for various purposes such as extraction, processing and analysing the data from Twitter. A total of 15,000 tweets from January 2015 to January 2021 were collected of the three sites using different key words. An exploratory design and data visualisation technique has been used to interpret results.

After data processing, 12,409 sentiments are extracted. Amongst the three tourists' spots, the greatest number of positive sentiments is for the Taj Mahal and Golden temple with approximately 25% each. While the most negative sentiment can be seen for the Red Fort (17%). Amongst the positive emotions, the maximum joy sentiment (12%) can be seen in the Golden Temple and trust (21%) in the Red Fort. In terms of negative emotions, fear (13%) can be seen in the Red fort. Overall, India's heritage sites have a positive sentiment (20%), which surpasses the negative sentiment (13%). And can be said that the overall polarity is towards positive.

This study provides a framework on how to use Twitter for tourism insights through text mining public sentiments and provides real- time insights from famous Indian heritage sites.

As hybrid organizations become increasingly common, the authors observe that some hybrid forms are becoming institutionalized and legitimated. The authors explore the implications of the institutionalization of hybridity, addressing both the internal tensions that plague many hybrids and the external tensions stemming from evaluator assessments and stakeholder uncertainty. The authors propose that institutionalization can dampen internal tensions associated with hybridity and also facilitate legitimation and acceptance by external audiences. The authors present identity as a useful theoretical lens through which to examine these questions, as identities are born from, but also have the potential to modify, existing institutional arrangements. The authors present directions for future research at the juncture of identity, hybridity, and institutionalization, suggesting potential avenues of inquiry in this productive stream of research.

Critics say cryptocurrencies are hard to predict and lack both economic value and accounting standards, while supporters argue they are revolutionary financial technology and a new asset class. This study aims to help accounting and financial modelers compare cryptocurrencies with other asset classes (such as gold, stocks and bond markets) and develop cryptocurrency forecast models.

Daily data from 12/31/2013 to 08/01/2020 (including the COVID-19 pandemic period) for the top six cryptocurrencies that constitute 80% of the market are used. Cryptocurrency price, return and volatility are forecasted using five traditional econometric techniques: pooled ordinary least squares (OLS) regression, fixed-effect model (FEM), random-effect model (REM), panel vector error correction model (VECM) and generalized autoregressive conditional heteroskedasticity (GARCH). Fama and French's five-factor analysis, a frequently used method to study stock returns, is conducted on cryptocurrency returns in a panel-data setting. Finally, an efficient frontier is produced with and without cryptocurrencies to see how adding cryptocurrencies to a portfolio makes a difference.

The seven findings in this analysis are summarized as follows: (1) VECM produces the best out-of-sample price forecast of cryptocurrency prices; (2) cryptocurrencies are unlike cash for accounting purposes as they are very volatile: the standard deviations of daily returns are several times larger than those of the other financial assets; (3) cryptocurrencies are not a substitute for gold as a safe-haven asset; (4) the five most significant determinants of cryptocurrency daily returns are emerging markets stock index, S&P 500 stock index, return on gold, volatility of daily returns and the volatility index (VIX); (5) their return volatility is persistent and can be forecasted using the GARCH model; (6) in a portfolio setting, cryptocurrencies exhibit negative alpha, high beta, similar to small and growth stocks and (7) a cryptocurrency portfolio offers more portfolio choices for investors and resembles a levered portfolio.

One of the tasks of the financial econometrics profession is building pro forma models that meet accounting standards and satisfy auditors. This paper undertook such activity by deploying traditional financial econometric methods and applying them to an emerging cryptocurrency asset class.

This paper attempts to contribute to the existing academic literature in three ways: Pro forma models for price forecasting: five established traditional econometric techniques (as opposed to novel methods) are deployed to forecast prices; Cryptocurrency as a group: instead of analyzing one currency at a time and running the risk of missing out on cross-sectional effects (as done by most other researchers), the top-six cryptocurrencies constitute 80% of the market, are analyzed together as a group using panel-data methods; Cryptocurrencies as financial assets in a portfolio: To understand the linkages between cryptocurrencies and traditional portfolio characteristics, an efficient frontier is produced with and without cryptocurrencies to see how adding cryptocurrencies to an investment portfolio makes a difference.

The purpose of this paper is to interrogate the nature and relevance of debates around the existence of, and ramifications arising from, the Anthropocene for accounting scholarship.

The paper’s aim is achieved through an in-depth analysis of the Anthropocene, paying attention to cross-disciplinary contributions, interpretations and contestations. Possible points of connection between the Anthropocene and accounting scholarship are then proposed and illuminated through a case study drawn from the seafood sector.

This paper develops findings in two areas. First, possible pathways for further development of how accounting scholarship might evolve by the provocation that thinking about the Anthropocene is outlined. Second, and through engagement with the case study, the authors highlight that the concept of stewardship may re-emerge in discussions about accountability in the Anthropocene.

The paper argues that accounting scholarship focused on social, environmental and sustainability concerns may be further developed by engagement with Anthropocene debates.

While accounting practice might have to change to deal with Anthropocene induced effects, this paper focuses on implications for accounting scholarship.

Human well-being is likely to be impacted if environmental impacts accelerate. In addition, an Anthropocene framing alters the understanding of nature–human interactions and how this affects accounting thought.

This is the first paper in accounting to seek to establish connections between accounting, accountability and the Anthropocene.

Managing biosphere reserves (BR) have become more challenging regarding the socio-cultural conflict between communities and BR administrators. For the past two decades, community participation (CP) has become the central narrative for BR management practices in Asia. This paper aims to set out to analyse the current literature because of the paucity of systematic reviews on CP in Asian BR. Also, it proffers possible solutions to enhance biosphere performance.

In total, 31 related studies were identified from the Scopus, Web of Science databases and materials from organisations in the field of practice of territorial conservation. Three themes emerged from the review – willingness to participate, encumbrances and possible solutions.

Factors that influence community willingness to participate in a BR, encumbrances facing the community and possible policy solutions to enhance CP in a BR in Asia were the three themes that emerged from the review. The factors that influence community willingness were categorised into the level of participants in education, perceived waste of time, no confidence of the outcome, okay with current management, land owned, household size and gender factors.

This paper’s recommendations were based on empirical literature reviewed systematically but do not compromise the robustness concerning BR management practices in Asia. It was established that to enrich the findings of this research, regional studies of CP in BR should be conducted, including primary source data using the mixed methods paradigm.

As part of the practical implications, recommendations were highlighted to enhance CP in BR. Also, the paper suggested that BR administrators should have two-way communication mechanisms, cross-sectoral participation and collaboration, implement locally-based solutions through full engagement of community members in decision-making.

This is probably the first systematic review paper on BR management practices in Asia. Filling the theoretical gap via systematic review was part of the significant contribution to CP in Asian BR.

This study aims to investigate the feasibility of employing a multi-objectives integer-programming model for effective allocation of resources for cyberfraud mitigation. The formulated objectives are the minimisation of the total allocation cost of the anti-fraud capacities and the maximisation of the forensic accounting capacities in all cyberfraud incident prone spots.

From the literature survey conducted and primary qualitative data gathered from the 17 licenced banks in South Africa on fraud investigators, the suggested fraud investigators are the organisation’s finance department, the internal audit committee, the external risk manager, accountants and forensic accountants. These five human resource capacities were considered for the formulation of the multi-objectives integer programming (MOIP) model. The MOIP model is employed for the optimisation of the employed capacities for cyberfraud mitigation to ensure the effective allocation and utilisation of human resources. Thus, the MOIP model is validated by a genetic algorithm (GA) solver to obtain the Pareto-optimum solution without the violation of the identified constraints.

The formulated objective functions are optimised simultaneously. The Pareto front for the two objectives of the MOIP model comprises the set of optimal solutions, which are not dominated by any other feasible solution. These are the feasible choices, which indicate the suitability of the MOIP to achieve the set objectives.

The results obtained indicate the feasibility of simultaneously achieving the minimisation of the total allocation cost of the anti-fraud capacities, or the maximisation of the forensic accounting capacities in all cyberfraud incident prone spots – or the trade-off between them, if they cannot be reached simultaneously. This study recommends the use of an iterative MOIP framework for decision-makers which may aid decision-making with respect to the allocation and utilisation of human resources.

The originality of this work lies in the development of multi-objectives integer-programming model for effective allocation of resources for cyberfraud mitigation.

State ownership has been common especially in industries with restricted competition. In Russia, state-controlled firms represent around 41 percent of the market value of all listed firms (Deloitte, 2015). Yet, there is a significant gap in the literature regarding the effects of various forms of government control in listed firms. The purpose of this paper is to fill this gap by exploring the impact of the complexity of state ownership and competition on the performance of Russian listed firms.

The sample consists of data for 72 firms (360 firm-years) in the Russian MOEX broad market index during 2011–2015. The complexity of state ownership is captured by studying forms of state control including majority/minority, direct/indirect, federal/regional, mixed structures and golden shares.

The authors find significant differences in performance relating to different forms of state ownership. State control is negatively related to firm valuation and the sales/employees ratio. Performance is weakest when state ownership takes the form minority, regional or direct ownership. State control through golden shares typically outperforms other state-controlled firms. The authors find indications of employment prioritization beyond the economical optimum. In addition, the relation between state ownership and profitability becomes positive in sectors where state firms appear to enjoy lower competition.

While the effects of state ownership have been studied on many markets, there is a lack of studies on the effects of different forms, or the complexity, of state ownership beyond direct and indirect ownership. The authors contribute to the literature on the performance effects of state ownership by studying a multitude of forms of governmental ownership as well as the role of competition in Russia. Especially the profitability of state-controlled firms is significantly affected by industry characteristics. Implications of the results are discussed both from firm and policy maker perspectives.