13,276 research outputs found

    Sustainability motivations and practices in small tourism enterprises in European protected areas

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    A survey of around 900 tourism enterprises in 57 European protected areas shows that small firms are more involved in taking responsibility for being sustainable than previously expected, including eco-savings related operational practices but also reporting a wide range of social and economic responsibility actions. Two-step cluster analysis was used to group the firms in three groups based on their motivations to be sustainable. Business driven firms implement primarily eco-savings activities and are commercially oriented. Legitimization driven firms respond to perceived stakeholder pressure and report a broad spectrum of activities. Lifestyle and value driven firms report the greatest number of environmental, social and economic activities. No profile has a higher business performance than average. The study has implications for policy programmes promoting sustainability behaviour change based primarily on a business case argument

    CSR marketing outcomes and branch managers' perceptions of CSR

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    Purpose The purpose of this paper is to analyze the role of bank branch managers’ perceptions of corporate social responsibility (CSR) in CSR marketing outcomes. Design/methodology/approach The paper proposes a causal model establishing that managers’ perceptions of CSR influence the perception of CSR held by the branch’s customers, which in turn directly affects customer satisfaction, customer trust, customer engagement and customer loyalty. The unit of analysis in this quantitative study is the bank branch. Two questionnaires were administered: one to branch managers and another to five customers in each branch. Findings Branch managers’ perceptions of CSR have a marked influence on customers’ perceptions of CSR, which again have a notable impact on the relationship variables studied: customer satisfaction, customer trust, customer engagement and customer loyalty. Research limitations/implications The sample was taken from two banks in the same country (Spain) and only five customers were interviewed in each branch. The type of customers analyzed should be taken into account since a growing number of customers now carry out all of their banking online and are less likely to visit their branch. Practical implications The results highlight the importance of adopting socially responsible actions not only in the bank as a whole, but also in individual branches. It would, therefore, seem crucial for high level bank executives not only to involve branch managers in the bank’s CSR strategy, but also to empower them to undertake CSR actions that involve the customers and local community with which they interact. Originality/value First, the paper reveals the differences within the same organization in the way its CSR strategy is implemented. Second, intermediary figures or supervisors are shown to have a key role in ensuring the organization’s CSR strategy is effective. Third, the study emphasizes the importance of customers’ perception of CSR in achieving the main outcomes of relationship marketing (satisfaction, trust, engagement and loyalty). Fourth, the methodology applied in the study is innovative in its construction of dyads in which the branch is the unit of analysis, enabling a comparison between the manager’s perceptions of CSR with that of five customers from the same branch. Fifth, the findings add to the knowledge of a particularly relevant sector in the recent economic crisis, namely, the retail banking industry

    Impact of mutual fund investment in indian equity market.

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    The mutual fund investments have emerged as important players in the Indian equity market in the recent past. This research makes an attempt to understand whether a relationship exists between Mutual Fund investment and Equity Market returns in India. The past ten years of data was analyzed with appropriate statistical tools to prove the impact of Mutual Fund Investments in Indian Equity Market. Markets become more efficient with the growing presence of institutional investors who predominantly go by fundamentals. The popular belief that fund inflows and returns are positively related. ( Warther, 1995) is also proved.Key words : Mutual Fund Flow, Equity Market, Sensex, Nifty.

    "Looking behind the veil": invisible corporate intangibles, stories, structure and the contextual information content of disclosure

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    Purpose – This paper aims to use a grounded theory approach to reveal that corporate private disclosure content has structure and this is critical in making "invisible" intangibles in corporate value creation visible to capital market participants. Design/methodology/approach – A grounded theory approach is used to develop novel empirical patterns concerning the nature of corporate disclosure content in the form of narrative. This is further developed using literature of value creation and of narrative. Findings – Structure to content is based on common underlying value creation and narrative structures, and the use of similar categories of corporate intangibles in corporate disclosure cases. It is also based on common change or response qualities of the value creation story as well as persistence in telling the core value creation story. The disclosure is a source of information per se and also creates an informed context for capital market participants to interpret the meaning of new events in a more informed way. Research limitations/implications – These insights into the structure of private disclosure content are different to the views of relevant information content implied in public disclosure means such as in financial reports or in the demands of stock exchanges for "material" or price sensitive information. They are also different to conventional academic concepts of (capital market) value relevance. Practical implications – This analysis further develops the grounded theory insights into disclosure content and could help improve new disclosure guidance by regulators. Originality/value – The insights create many new opportunities for developing theory and enhancing public disclosure content. The paper illustrates this potential by exploring new ways of measuring the value relevance of this novel form of contextual information and associated benchmarks. This connects value creation narrative to a conventional value relevance view and could stimulate new types of market event studies

    XML data integrity based on concatenated hash function

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    Data integrity is the fundamental for data authentication. A major problem for XML data authentication is that signed XML data can be copied to another document but still keep signature valid. This is caused by XML data integrity protecting. Through investigation, the paper discovered that besides data content integrity, XML data integrity should also protect element location information, and context referential integrity under fine-grained security situation. The aim of this paper is to propose a model for XML data integrity considering XML data features. The paper presents an XML data integrity model named as CSR (content integrity, structure integrity, context referential integrity) based on a concatenated hash function. XML data content integrity is ensured using an iterative hash process, structure integrity is protected by hashing an absolute path string from root node, and context referential integrity is ensured by protecting context-related elements. Presented XML data integrity model can satisfy integrity requirements under situation of fine-grained security, and compatible with XML signature. Through evaluation, the integrity model presented has a higher efficiency on digest value-generation than the Merkle hash tree-based integrity model for XML data

    RNN Language Model with Word Clustering and Class-based Output Layer

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    The recurrent neural network language model (RNNLM) has shown significant promise for statistical language modeling. In this work, a new class-based output layer method is introduced to further improve the RNNLM. In this method, word class information is incorporated into the output layer by utilizing the Brown clustering algorithm to estimate a class-based language model. Experimental results show that the new output layer with word clustering not only improves the convergence obviously but also reduces the perplexity and word error rate in large vocabulary continuous speech recognition
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