Amelia Manuti, Rosa Scardigno and Giuseppe Mininni
The paper argues that the diatextual analysis could be considered a psycho-cultural path of critical discourse analysis because it stresses the role of hermeneutical procedures in…
Abstract
Purpose
The paper argues that the diatextual analysis could be considered a psycho-cultural path of critical discourse analysis because it stresses the role of hermeneutical procedures in catching the inter-subjective nature of meanings. The purpose of this paper is to discuss these theoretical speculations in light with some empirical evidences coming from a discursive study exploring the construction of organizational identity through socialization practices.
Design/methodology/approach
Two focus group discussions were conducted, respectively, with retired workers and young workers employed in the same working organization to investigate how workers discursively shape their sense of belonging to the organization. Narratives of past and present membership were analyzed adopting the diatextual perspective, which was precious in tracking down the discursive traces of subjectivity, modality and argumentation emerging from their discourses.
Findings
Diatextual analysis was a precious tool to explore organizational identity through the different rhetoric that older and young workers used to make sense of it: “enchantment” vs “disenchantment.”
Research limitations/implications
The study was a case study. It involved few people and results cannot be generalized, but the main aim of the paper was to support qualitative methodology.
Practical implications
The implication of the study are precious to design formal socialization and human resource management practices better attuned with the need of workers.
Social implications
The social implications are connected with a wider revision of the organizational policies in terms of HRM.
Originality/value
The value of this paper is the discursive diatextual approach in organizational research.
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Amelia Manuti, Giuseppe Mininni and Stefania Attanasio
Narrative is believed to be a crucial component of sense-making in organizations, and previous research in the field suggests that multiple levels and forms of narrative are…
Abstract
Purpose
Narrative is believed to be a crucial component of sense-making in organizations, and previous research in the field suggests that multiple levels and forms of narrative are inherent to the definition of professional identities (Clarke et al., 2009; Ybema et al., 2009; Brown and Lewis, 2011). For example, narrative can be found in the stories told by organizational actors as they informally interact in the workplace, in the formalized basic assumptions that support organizational strategy-making, in the accounts people give of their work, and in the artifacts they produced and experienced while engaged in accomplishing tasks. The purpose of this paper is to consider narrative as a way of giving sense to organizational membership, of constituting an overall and possibly shared sense of direction, of focussing one’s professional identity, and of enabling and/or constraining the ongoing activities of actors. The context of the research was given by a group of sport federations enrolled within the Italian National Olympic Committee (CONI), which is the national most authoritative network of professional local sport organizations.
Design/methodology/approach
Participants involved in the study were 42 professional referees belonging to this network and active in different sport disciplines and 12 people from the CONI management. In-depth narrative interviews were collected in the aim to investigate the narrative cues revealing the organizational sense-making processes that animate the representation of this professional identity both at a subjective and at an organizational level. Data have been explored adopting the semiotic square and diatextual analysis as to highlight the strict relationship between text, context and interlocutors.
Findings
Data have been explored adopting the semiotic square and diatextual analysis as to highlight the strict relationship between text, context and interlocutors. Results showed that there was an evident gap between what the management formally defined as strategic vision, mission and cultural guidelines that actually shape the organizational identity of the CONI and what was concretely experienced by its actors, in this case the referees.
Originality/value
Most of the studies conducted in sport organizations focussed either on an intra-organizational level investigating the specific features of given professional categories such as athletes and/or coaches, or at an inter-organizational level, paying attention mostly to the marketing and networking strategies oriented toward stakeholders. On the other hand, most studies conducted on referees have devoted attention strictly to performance assessment, that, in line with a positivist approach, considered the latter as an output of situational and psychological variables (e.g. Marie, 1999; MacMahon et al., 2007). Conversely, the findings coming from the present study contributed to support the promotion of an alternative organizational approach, more specifically based on the strategic relevance of horizontal (within the federations) and vertical (between the federations and the center of the network) communication as to enhance the identification process which give sense to the organizational basic assumptions.
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Giuseppe Orlando, Rosa Maria Mininni and Michele Bufalo
The purpose of this study is to suggest a new framework that we call the CIR#, which allows forecasting interest rates from observed financial market data even when rates are…
Abstract
Purpose
The purpose of this study is to suggest a new framework that we call the CIR#, which allows forecasting interest rates from observed financial market data even when rates are negative. In doing so, we have the objective is to maintain the market volatility structure as well as the analytical tractability of the original CIR model.
Design/methodology/approach
The novelty of the proposed methodology consists in using the CIR model to forecast the evolution of interest rates by an appropriate partitioning of the data sample and calibration. The latter is performed by replacing the standard Brownian motion process in the random term of the model with normally distributed standardized residuals of the “optimal” autoregressive integrated moving average (ARIMA) model.
Findings
The suggested model is quite powerful for the following reasons. First, the historical market data sample is partitioned into sub-groups to capture all the statistically significant changes of variance in the interest rates. An appropriate translation of market rates to positive values was included in the procedure to overcome the issue of negative/near-to-zero values. Second, this study has introduced a new way of calibrating the CIR model parameters to each sub-group partitioning the actual historical data. The standard Brownian motion process in the random part of the model is replaced with normally distributed standardized residuals of the “optimal” ARIMA model suitably chosen for each sub-group. As a result, exact CIR fitted values to the observed market data are calculated and the computational cost of the numerical procedure is considerably reduced. Third, this work shows that the CIR model is efficient and able to follow very closely the structure of market interest rates (especially for short maturities that, notoriously, are very difficult to handle) and to predict future interest rates better than the original CIR model. As a measure of goodness of fit, this study obtained high values of the statistics R2 and small values of the root of the mean square error for each sub-group and the entire data sample.
Research limitations/implications
A limitation is related to the specific dataset as we are examining the period around the 2008 financial crisis for about 5 years and by using monthly data. Future research will show the predictive power of the model by extending the dataset in terms of frequency and size.
Practical implications
Improved ability to model/forecast interest rates.
Originality/value
The original value consists in turning the CIR from modeling instantaneous spot rates to forecasting any rate of the yield curve.
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Giuseppe Orlando, Rosa Maria Mininni and Michele Bufalo
The purpose of this paper is to model interest rates from observed financial market data through a new approach to the Cox–Ingersoll–Ross (CIR) model. This model is popular among…
Abstract
Purpose
The purpose of this paper is to model interest rates from observed financial market data through a new approach to the Cox–Ingersoll–Ross (CIR) model. This model is popular among financial institutions mainly because it is a rather simple (uni-factorial) and better model than the former Vasicek framework. However, there are a number of issues in describing interest rate dynamics within the CIR framework on which focus should be placed. Therefore, a new methodology has been proposed that allows forecasting future expected interest rates from observed financial market data by preserving the structure of the original CIR model, even with negative interest rates. The performance of the new approach, tested on monthly-recorded interest rates data, provides a good fit to current data for different term structures.
Design/methodology/approach
To ensure a fitting close to current interest rates, the innovative step in the proposed procedure consists in partitioning the entire available market data sample, usually showing a mixture of probability distributions of the same type, in a suitable number of sub-sample having a normal/gamma distribution. An appropriate translation of market interest rates to positive values has been introduced to overcome the issue of negative/near-to-zero values. Then, the CIR model parameters have been calibrated to the shifted market interest rates and simulated the expected values of interest rates by a Monte Carlo discretization scheme. We have analysed the empirical performance of the proposed methodology for two different monthly-recorded EUR data samples in a money market and a long-term data set, respectively.
Findings
Better results are shown in terms of the root mean square error when a segmentation of the data sample in normally distributed sub-samples is considered. After assessing the accuracy of the proposed procedure, the implemented algorithm was applied to forecast next-month expected interest rates over a historical period of 12 months (fixed window). Through an error analysis, it was observed that our algorithm provides a better fitting of the predicted expected interest rates to market data than the exponentially weighted moving average model. A further confirmation of the efficiency of the proposed algorithm and of the quality of the calibration of the CIR parameters to the observed market interest rates is given by applying the proposed forecasting technique.
Originality/value
This paper has the objective of modelling interest rates from observed financial market data through a new approach to the CIR model. This model is popular among financial institutions mainly because it is a rather simple (uni-factorial) and better model than the former Vasicek model (Section 2). However, there are a number of issues in describing short-term interest rate dynamics within the CIR framework on which focus should be placed. A new methodology has been proposed that allows us to forecast future expected short-term interest rates from observed financial market data by preserving the structure of the original CIR model. The performance of the new approach, tested on monthly data, provides a good fit for different term structures. It is shown how the proposed methodology overcomes both the usual challenges (e.g. simulating regime switching, clustered volatility and skewed tails), as well as the new ones added by the current market environment (particularly the need to model a downward trend to negative interest rates).
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Silvia Ivaldi, Annalisa Sannino and Giuseppe Scaratti
Building on the existing literature and on a series of interviews conducted in very diverse coworking spaces, this article attempts at analyzing coworking by focusing on the…
Abstract
Purpose
Building on the existing literature and on a series of interviews conducted in very diverse coworking spaces, this article attempts at analyzing coworking by focusing on the historical evolution and heterogeneity of its interpretations, as well as the plurality of its realization in practice and prospective developments.
Design/methodology/approach
The theoretical framework adopted is Cultural Historical Activity Theory – a dialectical approach which allows the study of human activities as historically evolving and complex systems which change under the impulse of their inner contradictions. The analysis presented here starts with an overview of the history of the theoretical elaborations and discussions of coworking. The authors then focus on the experiences and interpretations of this phenomenon as conveyed by coworkers and coworking managers in the north of Italy – one of the most active coworking areas in Europe.
Findings
Coworking first emerged as a way of promoting forms of work and organization that require simultaneous, multidirectional, and reciprocal work, as understood in contrast to forms that incorporate an established division of labor, demarcated communities, and formal and informal sets of rules. However, with time, coworking has evolved toward novel directions, giving rise to heterogeneous interpretations of it. Inquiry constitutes a deeper investigation of the heterogeneity of coworking. The take-away message here is that the prefix co- in coworking can be interpreted, through a play of words, to evoke multiple positions and views conveying internal contradictions.
Originality/value
The historical overview of coworking shows a strong differentiation and multisided interpretation of this phenomenon along two dimensions of historical development, namely, social and business, and outward and inward. The qualitative analysis of the interviews traces the different lived interpretations and conceptions of coworking. The analysis confirms, on the one hand, the complexity and heterogeneity described in the literature, and on the other hand, it enriches the literature by depicting the contradictory nature of the phenomenon, including how the historical and inner tensions of coworking are dynamically evolving in the concrete experiences reported by the managers and users in the coworking spaces.
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Silvia Ivaldi, Giuseppe Scaratti and Ezio Fregnan
This paper aims to address the relevance and impact of the fourth industrial revolution through a theoretical and practical perspective. The authors present both the results of a…
Abstract
Purpose
This paper aims to address the relevance and impact of the fourth industrial revolution through a theoretical and practical perspective. The authors present both the results of a literature review, highlighting the new competences required in innovative workplaces and a pivotal case, which explores challenges and skill models diffused in industry 4.0, describing the role of proper organizational learning processes in shaping new work cultures.
Design/methodology/approach
The paper aims to enhance the discussion around the 4.0 industrial revolution addressing both a theoretical framework, valorizing the existing scientific contributes and the situated knowledge, embedded in a concrete organizational context in which the fourth industrial revolution is experienced and practiced.
Findings
The findings acquired through the case study endorse what the scientific literature highlights about the impact, the new competences and the organizational learning paths. The conclusions address the agile approach to work as the more suitable way to place humans at the center of technological progress.
Research limitations/implications
The paper explores a specific organizational context, related to a high-tech multinational company, whose results illustrate the empirical evidence sustaining transformations in the working, professional and organizational cultures necessary to face the challenges of the fourth industrial revolution. The research was conducted with the managers of an international company and this a specific and limited target, even though relevant and interesting.
Practical implications
The paper connects the case with the general scenario, this study currently faces, to suggest hints and coordinates for crossing the unfolding situation and finding suitable matching between technological evolution and the development of new work and professional cultures and competences.
Social implications
Due to the acceleration that the COVID-19 has impressed to the use of digital technologies and remote connexion, the paper highlights some ambivalences that the quick evolution of the new technologies entails in relation to work and social conditions.
Originality/value
The opportunity to match both a literature analysis and an in-depth situated case study enhances the possibility to achieve a more articulated and complex view of the viral changes generated in the current context by the digitalization process.
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Michele Bufalo and Giuseppe Orlando
This study aims to predict overnight stays in Italy at tourist accommodation facilities through a nonlinear, single factor, stochastic model called CIR#. The contribution of this…
Abstract
Purpose
This study aims to predict overnight stays in Italy at tourist accommodation facilities through a nonlinear, single factor, stochastic model called CIR#. The contribution of this study is twofold: in terms of forecast accuracy and in terms of parsimony (both from the perspective of the data and the complexity of the modeling), especially when a regular pattern in the time series is disrupted. This study shows that the CIR# not only performs better than the considered baseline models but also has a much lower error than other additional models or approaches reported in the literature.
Design/methodology/approach
Typically, tourism demand tends to follow regular trends, such as low and high seasons on a quarterly/monthly level and weekends and holidays on a daily level. The data set consists of nights spent in Italy at tourist accommodation establishments as collected on a monthly basis by Eurostat before and during the COVID-19 pandemic breaking regular patterns.
Findings
Traditional tourism demand forecasting models may face challenges when massive amounts of search intensity indices are adopted as tourism demand indicators. In addition, given the importance of accurate forecasts, many studies have proposed novel hybrid models or used various combinations of methods. Thus, although there are clear benefits in adopting more complex approaches, the risk is that of dealing with unwieldy models. To demonstrate how this approach can be fruitfully extended to tourism, the accuracy of the CIR# is tested by using standard metrics such as root mean squared errors, mean absolute errors, mean absolute percentage error or average relative mean squared error.
Research limitations/implications
The CIR# model is notably simpler than other models found in literature and does not rely on black box techniques such as those used in neural network (NN) or data science-based models. The carried analysis suggests that the CIR# model outperforms other reference predictions in terms of statistical significance of the error.
Practical implications
The proposed model stands out for being a viable option to the Holt–Winters (HW) model, particularly when dealing with irregular data.
Social implications
The proposed model has demonstrated superiority even when compared to other models in the literature, and it can be especially useful for tourism stakeholders when making decisions in the presence of disruptions in data patterns.
Originality/value
The novelty lies in the fact that the proposed model is a valid alternative to the HW, especially when the data are not regular. In addition, compared to many existing models in the literature, the CIR# model is notably simpler and more transparent, avoiding the “black box” nature of NN and data science-based models.
设计/方法/方法
一般来说, 旅游需求往往遵循规律的趋势, 例如季度/月的淡季和旺季, 以及日常的周末和假期。该数据集包括欧盟统计局在打破常规模式的2019冠状病毒病大流行之前和期间每月收集的在意大利旅游住宿设施度过的夜晚。
目的
本研究旨在通过一个名为cir#的非线性单因素随机模型来预测意大利游客住宿设施的过夜住宿情况。这项研究的贡献是双重的:在预测准确性方面和在简洁方面(从数据和建模复杂性的角度来看), 特别是当时间序列中的规则模式被打乱时。我们表明, cir#不仅比考虑的基线模型表现更好, 而且比文献中报告的其他模型或方法具有更低的误差。
研究结果
当大量搜索强度指标被作为旅游需求指标时, 传统的旅游需求预测模型将面临挑战。此外, 鉴于准确预测的重要性, 许多研究提出了新的混合模型或使用各种方法的组合。因此, 尽管采用更复杂的方法有明显的好处, 但风险在于处理难使用的模型。为了证明这种方法能有效地扩展到旅游业, 使用RMSE、MAE、MAPE或AvgReIMSE等标准指标来测试cir#的准确性。
研究局限/启示
cir#模型明显比文献中发现的其他模型简单, 并且不依赖于黑盒技术, 例如在神经网络或基于数据科学的模型中使用的技术。所进行的分析表明, cir#模型在误差的统计显著性方面优于其他参考预测。
实际意义
这个模型作为Holt-Winters模型的一个拟议模型, 特别是在处理不规则数据时。
社会影响
即使与文献中的其他模型相比, 所提出的模型也显示出优越性, 并且在数据模式中断时对旅游利益相关者做出决策特别有用。
创意/价值
创新之处在于所提出的模型是Holt-Winters模型的有效替代方案, 特别是当数据不规律时。此外, 与文献中的许多现有模型相比, cir#模型明显更简单、更透明, 避免了神经网络和基于数据科学的模型的“黑箱”性质。
Diseño/metodología/enfoque
Normalmente, la demanda turística tiende a seguir tendencias regulares, como temporadas altas y bajas a nivel trimestral/mensual y fines de semana y festivos a nivel diario. El conjunto de datos consiste en las pernoctaciones en Italia en establecimientos de alojamiento turístico recogidas mensualmente por Eurostat antes y durante la pandemia de COVID-19, rompiendo los patrones regulares.
Objetivo
El presente estudio pretende predecir las pernoctaciones en Italia en establecimientos de alojamiento turístico mediante un modelo estocástico no lineal de un solo factor denominado CIR#. La contribución de este estudio es doble: en términos de precisión de la predicción y en términos de parsimonia (tanto desde la perspectiva de los datos como de la complejidad de la modelización), especialmente cuando un patrón regular en la serie temporal se ve interrumpido. Demostramos que el CIR# no sólo aplica mejor que los modelos de referencia considerados, sino que también tiene un error mucho menor que otros modelos o enfoques adicionales de los que se informa en la literatura.
Resultados
Los modelos tradicionales de previsión de la demanda turística pueden enfrentarse a desafíos cuando se adoptan cantidades masivas de índices de intensidad de búsqueda como indicadores de la demanda turística. Además, dada la importancia de unas previsiones precisas, muchos estudios han propuesto modelos híbridos novedosos o han utilizado diversas combinaciones de métodos. Así pues, aunque la adopción de enfoques más complejos presenta ventajas evidentes, el riesgo es el de enfrentarse a modelos poco manejables. Para demostrar cómo este enfoque puede extenderse de forma fructífera al turismo, se comprueba la precisión del CIR# utilizando métricas estándar como RMSE, MAE, MAPE o AvgReIMSE.
Limitaciones/implicaciones de la investigación
El modelo CIR# es notablemente más sencillo que otros modelos encontrados en la literatura y no se basa en técnicas de caja negra como las utilizadas en los modelos basados en redes neuronales o en la ciencia de datos. El análisis realizado sugiere que el modelo CIR# supera a otras predicciones de referencia en términos de significación estadística del error.
Implicaciones prácticas
El modelo propuesto destaca por ser una opción viable al modelo Holt-Winters, sobre todo cuando se trata de datos irregulares.
Implicaciones sociales
El modelo propuesto ha demostrado su superioridad incluso cuando se compara con otros modelos de la bibliografía, y puede ser especialmente útil para los agentes del sector turístico a la hora de tomar decisiones cuando se producen alteraciones en los patrones de datos.
Originalidad/valor
La novedad radica en que el modelo propuesto es una alternativa válida al Holt-Winters especialmente cuando los datos no son regulares. Además, en comparación con muchos modelos existentes en la literatura, el modelo CIR# es notablemente más sencillo y transparente, evitando la naturaleza de “caja negra” de los modelos basados en redes neuronales y en ciencia de datos.