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  • The effect of electronic word of mouth communications on intention to buy: A meta-analysis

    Ismagilova, Elvira; Slade, E.L.; Rana, N.P.; Dwivedi, Y.K. (2019)
    The aim of this research is to synthesise findings from previous studies by employing weight and meta-analysis to reconcile conflicting evidence and draw a “big picture” of eWOM factors influencing consumers’ intention to buy. By using the findings from 69 studies, this research identified best (e.g. argument quality, valence, eWOM usefulness, trust in message), promising (e.g. eWOM credibility, emotional trust, attitude towards website) and least effective (e.g. volume, existing eWOM, source credibility) predictors of intention to buy in eWOM research. Additionally, the effect size of each predictor was calculated by performing meta-analysis. For academics, understanding what influences consumers’ intention to buy will help set the agenda for future research directions; for practitioners, it will provide benefit in terms of practical guidance based on detailed analysis of specific factors influencing consumers’ intention to buy, which could enhance their marketing activities.
  • Mapping hotel brand positioning and competitive landscapes by text-mining user-generated content

    Hu, F.; Trivedi, Rohitkumar (2019)
    This study uncovers hotel brand positioning and competitive landscape mapping by text-mining user-generated content (UGC). Rather than relying on a single dimension of consumer evaluation, the current study detects brand attributes by using both customer preferences as well as perceptual performance to develop meaningful insights. For this, the study combines content analysis and repertory grid analysis (RGA) to answer three key research issues. 111,986 hotel reviews from two biggest Chinese cities are used to explore and visualize the competitive landscape of six selected hotel brands across three hotel categories. Findings from the study will not only advance the existing literature on brand positioning and competitive landscape mapping but also help practitioners in developing brand positioning strategies to fight competitors within and across hotel categories.
  • Investment decisions with finite-lived collars

    Adkins, Roger; Paxson, D.; Pereira, P.J.; Rodrigues, A. (2019-06)
    The duration of most collar arrangements provided by governments to encourage early investment in infrastructure, renewable energy facilities, or other projects with social objectives are finite, not perpetual. We extend the previous literature on collar-style arrangements by providing an analytical solution for the idle and active values, as well as the investment triggers, for projects where collars are either finite-lived or retractable. What is the difference between these types of arrangements with their perpetual counterpart? Lots, including different vega signs, and substantially different values for different current price levels. Often, finite and retractable collars justify earlier investment timing than perpetual collars. In general, we demonstrate that the finite-lived and retractable versions have a significant impact on optimal behavior, relative to the perpetual case. An important consideration when negotiating the floors, ceilings, and duration (or signalling the expected duration) of a finite or a retractable collar is the current price level of the output and its expected volatility over the life of the contract.
  • Machine learning approach to auto-tagging online content for content marketing efficiency: A comparative analysis between methods and content type

    Salminen, J.; Yoganathan, Vignesh; Corporan, J.; Jansen, B.J.; Jung, S.-G. (2019-08)
    As complex data becomes the norm, greater understanding of machine learning (ML) applications is needed for content marketers. Unstructured data, scattered across platforms in multiple forms, impedes performance and user experience. Automated classification offers a solution to this. We compare three state-of-the-art ML techniques for multilabel classification - Random Forest, K-Nearest Neighbor, and Neural Network - to automatically tag and classify online news articles. Neural Network performs the best, yielding an F1 Score of 70% and provides satisfactory cross-platform applicability on the same organisation's YouTube content. The developed model can automatically label 99.6% of the unlabelled website and 96.1% of the unlabelled YouTube content. Thus, we contribute to marketing literature via comparative evaluation of ML models for multilabel content classification, and cross-channel validation for a different type of content. Results suggest that organisations may optimise ML to auto-tag content across various platforms, opening avenues for aggregated analyses of content performance.
  • How detailed product information strengthens eco-friendly consumption

    Osburg, V.-S.; Yoganathan, Vignesh; Brueckner, S.; Toporowski, W. (2019)
    Purpose: Whilst many studies consider labelling as means of aggregated communication of environmental product features, the presentation of detailed product information seems a promising alternative. However, the mechanisms through which detailed product information takes effect on consumers requires better understanding. This study empirically develops a framework that focuses on consumers’ perceived usefulness of, and trust in, detailed product information, whilst also considering the role of environmental self-identity. This understanding will help businesses to further stimulate eco-friendly consumption. Methodology: Structural equation modelling and conditional process analysis are utilised to test hypotheses based on a sample of 279 respondents to a German online survey. Findings: Results show that the perceived usefulness of product information has a positive effect on purchase intention, and this effect is intensified by an individual’s environmental self-identity. Furthermore, for consumers with high environmental self-identity, the effect of perceived usefulness of product information on purchase intention is mediated in turn by trust in detailed product information and resistance to negative information. Originality/Value: This study contributes to the debate on the role of product information in ethical consumption by showing how detailed product information gives rise to favourable behavioural outcomes. When detailed information is perceived as being useful, it can affect purchase intention through greater trust and an increased resistance to negative information. Further, detailed product information appears beneficial for both, the mass market and specific segments with high environmental self-identity. Hence, this study empirically establishes the effects of detailed product information on consumer decision-making, thus informing sustainability-related marketing theory and practice.
  • Animal and Human Models in Advertising: How can we influence the consumer decision making journey?

    Trivedi, Rohitkumar; Teichert, T. (2019)
    For decades, animals have been widely used in advertisements, and yet little is known about the effects on consumer reactions along the entire purchase decision process. This study disentangles the effects of using animal stimuli in isolation or jointly with a human model in print advertisements. Empirical evidence is derived from 126,220 consumer evaluations of 302 actual print advertisements across 18 product categories. Animals do not only support a positive attitude change, they also influence how products integrate into consumers´ relevant set and the purchase intention by itself. By comparison, female consumers react more pronounced than their male counterparts on animal stimuli. However, it should be avoided to combine an animal stimulus with a human model to preserve a better influence over consumer reaction.
  • Going green, going clean: Lean-green sustainability strategy and firm growth

    Lartey, T.; Yirenkyi, D.O.; Adomako, Samuel; Danso, A.; Amankwah-Amoah, J.; Alam, A. (Wiley, 2019)
    Despite the widespread recognition of the paybacks of “going green” and “going clean”, limited research has focused on the impact of lean-green strategy on firm growth. In this study, we contribute to strategy and environmental sustainability literatures by investigating the possibility that the influence on lean-green strategy and firm growth is driven by different levels of industry competition, managerial power and family ties. Using panel data from 732 firms in four major industrialised economies (the US, Germany, France and the UK), we found that lean-green strategy positively relates to firm growth and this relationship is amplified at higher levels of competition, managerial power and family ties. Theoretical and practical implications of the study are also discussed.
  • Pricing of time-varying illiquidity within the Eurozone: Evidence using a Markov switching liquidity-adjusted capital asset pricing model

    Grillini, S.; Ozkan, A.; Sharma, Abhijit; Al Janabi, M.A.M. (2019)
    This paper investigates time-varying characteristics of illiquidity and the pricing of its risk using a liquidity-adjusted capital asset pricing model (L-CAPM). Collecting data from a pool of Eurozone countries between 1990 and 2018, we employ Markov switching models to assess the degree of persistence of illiquidity shocks. Contrary to prior research, which largely makes use of autoregressive (AR) processes, we provide strong evidence that illiquidity is time-varying and the persistence of shocks determines two distinct regimes characterised by high and low illiquidity. We assess pricing of illiquidity risk by developing and empirically testing a conditional L-CAPM model, where different regimes constitute priced risk factors for the cross-section of stock returns. We extend previous unconditional versions of L-CAPM models and we show that the various channels through which illiquidity affects asset returns and price of risks are time-varying. We find strong support for our conditional L-CAPM and our results are robust to alternative specifications and estimation techniques. These findings have important implications for portfolio management practices and are relevant to portfolio and risk managers and regulatory institutions.
  • Is Radiative Forcing Cointegrated with Temperature? A Further Examination Using a Structural Time Series Approach

    Balcombe, K.; Fraser, I.M.; Sharma, Abhijit (2019)
    This paper re-examines the long-run relationship between radiative forcing (including emissions of carbon dioxide, sulphur oxides, methane, and solar radiation) and temperatures from a structural time series modeling perspective. We assess whether forcing measures are cointegrated with global temperatures using the structural time series approach.
  • Role of big data and social media analytics for business to business sustainability: A participatory web context

    Sivarajah, Uthayasankar; Irani, Zahir; Gupta, S.; Mahroof, Kamran (2019)
    The digital transformation is an accumulation of various digital advancements, such as the transformation of the web phenomenon. The participatory web that allows for active user engagement and gather intelligence has been widely recognised as a value add tool by organisations of all shapes and sizes to improve business productivity and efficiency. However, its ability to facilitate sustainable business-to-business (B2B) activities has lacked focus in the business and management literature to date. This qualitative research is exploratory in nature and fills this gap through findings arising from interviews of managers and by developing taxonomies that highlight the capability of participatory web over passive web to enable different firms to engage in business operations. For this purpose, two important interrelated functions of business i.e. operations and marketing have been mapped against three dimensions of sustainability. Consequently, this research demonstrates the ability of big data and social media analytics within a participatory web environment to enable B2B organisations to become profitable and remain sustainable through strategic operations and marketing related business activities. The research findings will be useful for both academics and managers who are interested in understanding and further developing the business use of participatory web tools to achieve business sustainability. Hence, this may be considered as a distinct way of attaining sustainability.
  • Achieving Agility in Evacuation Operations: An Evidence-Based Framework

    Rodríguez-Espíndola, O.; Despoudi, S.; Albores, P.; Sivarajah, Uthayasankar (2019)
    There is an agreement among European countries about the need to achieve efficient, effective and responsive evacuations as part of disaster management. Evacuations face uncertain and dynamic conditions, which often challenge the expectations at the planning stage. This research looks at the adoption of agility in evacuation operations. Managers involved in disaster operations in three countries were interviewed to identify current practices and needs during evacuations. This article looks at the potential of beneficiary engagement, staff and information, cooperation, and fitness for change to incorporate agile practices at each one of the stages of evacuation planning. The purpose is to provide an Agile Evacuation Operations (AEO) evidence-based framework to inform theory and practice. The analysis provided shows that along with current practices it is important to engage the beneficiaries more closely, empower and train the staff to react to unexpected conditions, and take advantage of local knowledge to enhance operations.
  • B2B brands on Twitter: Engaging users with a varying combination of social media content objectives, strategies, and tactics

    Juntunen, M.; Ismagilova, Elvira; Oikarinen, E.-L. (2019)
    The objective of this research is to increase understanding about B2B company-led user engagement on social media content. Building on hierarchy-of-effects (HoE) theory, we explore how the world’s leading B2B companies use content objectives (why), strategies (how), and tactics (what) on Twitter. We first integrate B2B advertising and social media research on companies’ content objectives, strategies, and tactics. Then, using qualitative analyses, we examine the existence of objectives, strategies, and tactics in the most engaging tweets (N=365) of the worlds’ ten leading B2B brands, covering five industries, in 2017. Finally, we quantitatively examine how the use of diverse objectives and strategies differs between the most engaging tweets (N=318) and least engaging tweets (N=229) of the companies in 2018. The companies use objectives, strategies and tactics that relate to creating awareness, knowledge and trust, interest, and liking in the majority of their most and least engaging tweets, and express preference, conviction and purchase aspects much less. Differences exist in general, industry-wise, and company-wise. The study is a rare attempt to integrate the extant B2B advertising and social media research, and compare the most and least engaging B2B social media content.
  • Balancing Digital-By-Default with Inclusion: A Study of the Factors Influencing E-Inclusion in the UK

    Al-Muwil, A.; Weerakkody, Vishanth J.P.; El-Haddadeh, R.; Dwivedi, Y. (2019)
    Digital inclusion research has been critically important in drawing an understanding of how policies, society, organisations, and information technologies can all come together within a national environment that aspires to be a digital nation. This research aims to examine the factors influencing e-Inclusion in the UK within a digital-by-default policy for government services. This study is pursued through combining the Decomposed Theory of Planned Behaviour (DTPB) with Use and Gratification Theory (U&G) and conducting a self-administered survey targeting 510 Internet users to study the level of citizens engagement with e-government services in the UK. By incorporating gratification, trust, risk and external factors (i.e. self-efficacy, accessibility, availability, affordability) within DTPB, the proposed model of e-Inclusion used in the paper demonstrates a considerable explanatory and predictive power and offers a frame of reference to study the acceptance and usage of e-government within a national context where nearly all government transactions are digital-by-default. The findings revealed six dimensions as key inhibitors for e-Inclusion, namely: demographic, economic, social, cultural, political, and infrastructural.
  • Live football and tourism expenditure: match attendance effects in the UK

    Sharma, Abhijit; Rudkin, Simon (2019-04)
    The inbound tourist expenditure generating role of football (soccer), particularly the English Premier League 15 (EPL) is evaluated. An enhanced economic and management understanding of the role of regular sporting fixtures emerges, as well as quantification of their impact. Expenditure on football tickets is isolated to identify local economic spillovers outside the stadium walls. Using the UK International Passenger Survey, unconditional quantile regressions (UQR) is used to evaluate the distributional impact of football attendance on tourist expenditures. Both total expenditure and a new measure which adjusts expenditures for football ticket prices are considered. UQR is a novel technique which is as yet underexploited within sport economics and confers important methodological advantages over both OLS and quantile regressions. Significant cross quantile variation is found. High spending football fans spend more, even after ticket prices are excluded. Surprisingly, spending effects owing to attendance are strongest for those who overall spend the least, confirming the role of sport as a generator of tourist expenditure unlike most others. Though the attendance effect is smaller for higher aggregate spenders, there is nevertheless a significant impact across the distribution. Distributional expenditure impacts highlight clear differentials between attendance by high and low spenders. Similar analysis is applicable to other global brands such as the National Football League (NFL) in the United States (American football) and the Indian Premier (cricket) League. The EPL’s global popularity can be leveraged for achieving enhanced tourist expenditure.
  • Institutional voids, international learning effort and internationalization of emerging market new ventures

    Adomako, Samuel; Amankwah-Amoah, J.; Dankwah, G.O.; Danso, A.; Donbesuur, F. (2019)
    Much of the existing scholarly works portray institutional voids (IVs) in emerging economies as impeding forces against the development of new ventures. However, little attention has been paid to how such voids generate positive outcomes in emerging market new ventures. Drawing on the institutional theory, we propose IVs as crucial enablers of new venture internationalization. In addition, we investigate both how and when IVs enhance the degree to which new ventures internationalize by examining international learning effort (ILE) as a mediator and two domestic market environmental factors (i.e., environmental dynamism and competitive intensity) as important contingencies. We test our moderated mediation model using primary data gathered from 211 new ventures from Ghana. We found that ILE mediates the relationship between IVs and new venture internationalization and that both environmental dynamism and competitive intensity moderate the indirect relationship between home-country IVs and new venture internationalization. We discuss the theoretical and practical implications of this study.
  • Factors contributing to the strength of national patent protection and enforcement after TRIPS

    Papageorgiadis, Nikolaos; Wang, Chengang; Magkonis, Georgios (2019)
    In this paper we study the determinants of the strength of patent enforcement in 43 member countries of the World Trade Organization (WTO) between 1998 and 2011, a period after the signing of the Trade-Related Aspects of Intellectual Property Rights (TRIPS) agreement. We do so by building on and expanding the seminal work of Ginarte and Park (1997) on the pre-TRIPS determinants of patent rights in the years 1960-1990. We find that in the years after TRIPS was signed, the strength of patent enforcement of a country is positively determined by two variables that signify the usage of the patent and intellectual property system, and the number of patent and trademark applications. We also find that the level of research and development expenditure, the quality of human capital, and the level of development of a country have positive effects on the strength of the enforcement of patent law in practice. Intellectual property rights enforcement is one of the key investment-related policies included in the United Nations Conference on Trade and Development (UNCTAD) Investment Policy Framework for Sustainable Development. Identifying the determinants of strong patent systems will help policymakers at the national and supranational levels to design and implement effective policies that strengthen national patent systems, thereby enhancing economic benefits such as greater levels of commercialization of intangible assets and greater levels of international trade and investment.
  • Testing the predictive ability of corridor implied volatility under GARCH models

    Lu, Shan (2019-06)
    This paper studies the predictive ability of corridor implied volatility (CIV) measure. It is motivated by the fact that CIV is measured with better precision and reliability than the model-free implied volatility due to the lack of liquid options in the tails of the risk-neutral distribution. By adding CIV measures to the modified GARCH specifications, the out-of-sample predictive ability of CIV is measured by the forecast accuracy of conditional volatility. It finds that the narrowest CIV measure, covering about 10% of the RND, dominate the 1-day ahead conditional volatility forecasts regardless of the choice of GARCH models in high volatile period; as market moves to non volatile periods, the optimal width broadens. For multi-day ahead forecasts narrow and mid-range CIV measures are favoured in the full sample and high volatile period for all forecast horizons, depending on which loss functions are used; whereas in non turbulent markets, certain mid-range CIV measures are favoured, for rare instances, wide CIV measures dominate the performance. Regarding the comparisons between best performed CIV measures and two benchmark measures (market volatility index and at-the-money Black–Scholes implied volatility), it shows that under the EGARCH framework, none of the benchmark measures are found to outperform best performed CIV measures, whereas under the GARCH and NAGARCH models, best performed CIV measures are outperformed by benchmark measures for certain instances.

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