Do special issues offer something special? An overview of research trends in Telecommunications Policy special issues

This study explores the value of special issues by analyzing the characteristics of special issues of Telecommunications Policy (TP). Specifically, this study examines the status of special issue publications, the characteristics of their articles compared with those of general issues, and the factors affecting article citations. For the analysis, all information on TP articles published from 1976 to 2018 was collected from the Scopus database. A comparative analysis as well as a negative binomial regression were conducted on papers published after 1994, when the first special issue was published. The results show that special issues are distinguished from general issues by various characteristics, such as multinational author collaboration, number of references, keywords, and funding. While general issue papers are more frequently cited in academia, special issue papers show better performance in terms of online captures and social media sharing. Moreover, the smaller number of variables affects the frequency of citations in the case of special issues, revealing that content and format are more influential than author factors.     

Complex Network of Aviation E-Services in the Belt and Road Initiative: A Heuristic Study of Small Data based on Block Modeling

ABSTRACT

The aviation e-service system is an important part of support for business communication in regions covered by Belt and Road initiative. In exploring the role of airline companies in this system, we examine the structure of the network, which consists of airlines interconnections based on small data of individual attributes of aviation companies in aviation e-services, and study these interconnections across different groups using block modeling. The heuristic solution of airline companies in development of international communication and cooperation is further discussed. Among our policy implications for global managers, we suggest the enhancement of cross-regional cooperation among airlines.     

Addressing the sustainable development through sustainable procurement: What factors resist the implementation of sustainable procurement in Pakistan?

Sustainable Public Procurement is an integral part of sustainable development because of ever increasing government expenditures. Most of the developing countries lack the required infrastructure which may support public sector sustainability. The aim of this study is to assess the critical factors which resist the implementation of sustainable procurement in public sector of Pakistan. We used Interpretive Structural Model to investigate and rank the interrelationships among different factors of sustainable procurement. With the help of literature and Likert scale instrument, we found twelve key barriers that resist sustainable procurement implementation. We also examined tender documents of 75 different public sector universities of Pakistan but found absence of sustainability element in the documents. External factors namely government legislation and stakeholders' pressure are found most critical barriers as compared to inter organizational factors. The study is also important to highlight the hurdles in the way of sustainable development. First, the government must introduce rules and regulations to implement the sustainable procurement. Stakeholders and donors must put pressure on organizations for adopting sustainable procurement. Sustainability education should be made mandatory part of curriculum and employees should be given regular training on sustainability. Further, public procurement policies at government and institutional levels are required to be revisited towards a circular economy.     

From rationality to hyperreality: paradigm poker

This paper, following McGoun's (1997) seminal article comparing the economy of financial securities to a hyperreal poker game, argues that finance and accounting researchers should take the “linguistic turn” that has rejuvenated theory and research in many, if not most, of the social science and humanities in recent decades. In general terms, this means following Ludwig Wittgenstein's language game paradigm rather than Karl Popper's scientific deductive hypothesis testing methodology. The paper illustrates this by drawing on some of Jean Baudrillard's' ideas, particularly his concept of hyperreality and his phases of the image theoretic.The paper presents a poststructuralist genealogical analysis of the radical ruptures and reformulation of the meaning attributed to the accounting sign of earnings over the feudal, counterfeit, production, and simulation eras. It concludes that, as with many other signs in contemporary society, the earnings sign no longer has any relationship with, nor does it any longer refer to, any real or intrinsic profit but instead floats ungrounded in today's financial economy.The paper recommends that researchers in finance and accounting adopt paradigms from literary theory, semiotics, linguistics, and semiology rather than continue to rely on economics-based theory, which has lost its power for explaining and predicting happenings in today's financial economy of self-referencing models and images.     

Formal business process engineering based on graph grammars

Designing and managing a company's specific landscape and its business processes has been identified as a great challenge for several years. Business processes are highly dynamic and distributed and can only rarely be planned, modeled and analyzed completely. For a computer-aided business process system, which supports the designing and managing process, first of all a powerful uniform formalism is necessary, where all necessary knowledge concerning company's and its processes can be represented. In this paper we will concentrate on the introduction of such a formal methodology to describe business processes, company organization structures and information technology structures in one uniform formalism. The ideas we use are mainly based on methods from graph grammars, process management, Artificial Intelligence and business process (re)engineering.     

Inferential Causal Models: Integrating Quality & Quantity

In-depth data analysis plus statistical modeling can produce inferentialcausal models. Their creation thus combines aspects of analysis by close inspection,that is, reason analysis and cross-tabular analysis, with statistical analysis procedures,especially those that are special cases of the generalized linear model (McCullaghand Nelder, 1989; Agresti, 1996; Lindsey, 1997). This paper explores some of the roots of this combined method and suggests some new directions. An exercise clarifies some limitations of classic reason analysis by showing how the cross tabulation of variables with controls for test factors may produce better inferences. Then, given the cross tabulation of several variables, by explicating Coleman effect parameters, logistic regressions, and Poisson log-linear models, it shows how generalized linear models provide appropriate measures of effects and tests of statistical significance. Finally, to address a weakness of reason analysis, a case-control design is proposed and an example is developed.     

The Multilevel Approach to Repeated Measures for Complete and Incomplete Data

Repeated measurements often are analyzed by multivariate analysis of variance (MANOVA). An alternative approach is provided by multilevel analysis, also called the hierarchical linear model (HLM), which makes use of random coefficient models. This paper is a tutorial which indicates that the HLM can be specified in many different ways, corresponding to different sets of assumptions about the covariance matrix of the repeated measurements. The possible assumptions range from the very restrictive compound symmetry model to the unrestricted multivariate model. Thus, the HLM can be used to steer a useful middle road between the two traditional methods for analyzing repeated measurements. Another important advantage of the multilevel approach to analyzing repeated measures is the fact that it can be easily used also if the data are incomplete. Thus it provides a way to achieve a fully multivariate analysis of repeated measures with incomplete data. This revised version was published online in June 2006 with corrections to the Cover Date.     

The Random Walk Hypothesis in the Emerging Indian Stock Market

This paper examines the random walk hypothesis in the emerging Indian stock market using daily data on individual stocks. The statistical evidence in this paper rejects the random walk hypothesis. The results suggest that daily returns earned by individual stocks and by an equally weighted portfolio show significant non–linear dependence and persistent volatility effects. The non–linear dependence takes the form of ARCH–type conditional heteroskedasticity and does not appear to be caused by nonstationarity of underlying economic variables. Though conditional volatility is time varying, it does not explain expected returns.