Elisa Battistoni

Analytic Hierarchy Process for New Product Development

The success of a New Product Development (NPD) process strongly depends on the deep comprehension of market needs and Analytic Hierarchy Process (AHP) has been commonly used to find weights for customers preferences. AHP best practices suggest that low-consistency respondents should be considered untrustworthy; however, in some NPD cases – such as the one presented here – this stake can be extremely big. This paper deals with the usage of AHP methodology to define the weights of customer needs connected to the NPD process of a typical impulse buying good, a snack. The aim of the paper is to analyse in a critical way the opportunity to exclude or include non-consistent respondents in market analysis, addressing the following question: should a non-consistent potential customer be excluded from the analysis due to his inconsistency or should he be included because, after all, he is still a potential consumer? The chosen methodological approach focuses on evaluating the compatibility of weight vectors among different subsets of respondents, filtered according to their consistency level. Results surprisingly show that weights do not significantly change when non-consistent respondents are excluded.

Prominent Determinants of Consumer-Based Brand Equity

In this paper we investigate the most prominent drivers of brand equity, from a consumer-based point of view. We present a new approach for measuring brand equity, which can be applied regardless of the brand sector and is based on the Analytic Hierarchy Process. This approach has the main advantage of allowing for comparisons to be made between non-directly measurable elements and also has the advantage of enabling the ranking of intangible criteria, such as consumers feelings or purchase intentions. We focus on the fashion industry, since we believe in the higher value of our approach when applied to brands which offer products with less tangible characteristics. Thanks to a case study – which involved about 250 interviewees – we succeed in finding and prioritizing the elements which can have an impact on the brand value. We also provide a global ranking for three apparel brands: Gap, H&M and Zara. The results from our model are consistent with other popular ratings and can be extremely useful for brand managers.

An Analysis of the Effect of Operations Management Practices on Performance

In this paper we investigate the possible relationships among some optimization techniques used in Operations Management and the performance of SMEs that operate in the manufacturing sector. A model based on the Structural Equation Modelling (SEM) approach is used to analyse a dataset of small and medium-sized Italian enterprises. The model is expressed by a system of simultaneous equations and is solved through regression analysis. Taking advantage of the contributions presented previously, we focus our research on the Italian economy, highlighting the importance of Operations Management practices, which are relevant drivers of these firms performances.

Using four different online media sources to forecast the crude oil price

This study looks for signals of economic awareness on online social media and tests their significance in economic predictions. The study analyses, over a period of 2u2009years, the relationship between the West Texas Intermediate daily crude oil price and multiple predictors extracted from Twitter; Google Trends; Wikipedia; and the Global Data on Events, Location and Tone (GDELT) database. Semantic analysis is applied to study the sentiment, emotionality and complexity of the language used. Autoregressive Integrated Moving Average with Explanatory Variable (ARIMAX) models are used to make predictions and to confirm the value of the study variables. Results show that the combined analysis of the four media platforms carries valuable information in making financial forecasting. Twitter language complexity, GDELT number of articles and Wikipedia page reads have the highest predictive power. This study also allows a comparison of the different fore-sighting abilities of each platform, in terms of how many days ahead a platform can predict a price movement before it happens. In comparison with previous work, more media sources and more dimensions of the interaction and of the language used are combined in a joint analysis.

Key-Roles in VLEs: A Metric Based on Social Network Analysis

In this paper we analyze an e-learning course for managerial education over 3 years making use of the social network analysis. Our aim is to represent the knowledge flows within a virtual learning environment and to identify some key-roles, previously highlighted by Cross and Prusak (2002) in organizational contexts. Our methodology shows the specific contribution brought by each actor to the knowledge development in a community, so it can support teachers in the development of their teaching strategies.

Leveraging on informal networks for organizational change

The dynamic and uncertain scenarios that economic organizations have to face force them to deeply rethink themselves and their structure through an internal innovation process aimed at making them more reactive and proactive. Organizations can be viewed as systems whose components (people, team, groups, organizations) are joined by formal and informal relationships, and any process of internal change requires complex negotiations based on them. It is therefore of paramount importance to perceive accurately the network of informal relationships and to actively manage them. On the basis of the concept of distance between individuals and making use of the social network analysis we provide a methodology for determining both the actual network of relationships that links all actors in the organization and an index (IDO, Informality Degree of Organizations) able to measure the level of informality prevailing within an organization. IDO index gives both theoretical and practical indications to the management for successfully implementing an internal change policy.

European Integration and Telecommunication Productivity Convergence

On May 1st, 2004 ten countries entered the European Union (EU), thus realising the greatest enlargement since its establishment. The aim of this paper is to determine whether in the period 1995–2002, the telecommunication industries of these newly entered countries have been involved in a catching-up process towards the levels reached by the countries already in the EU.

What Makes You Popular: Beauty, Personality or Intelligence?

This study explores the determinants of popularity within friendship and advice networks. We involved almost 200 college students in an experiment to predict how personality traits, self-monitoring, creativity, intelligence, energy, and beauty influence the development of friendship and advice networks. Our results indicate that physical attractiveness is a key to develop both friendship and task-related interactions, whereas perceived intelligence and creativity play an important role in the advice network. Our findings seem to support the idea that there might be a kernel of truth in the stereotype that attractiveness correlates with positive social traits and successful outcomes.

Exploiting the Potential Value of Over-the-counter Drugs Leveraging on Brand Equity: An Analytic Network Process Approach

We propose a network model to identify the main drivers of consumer-based brand equity. We apply our research to assess the value of three over-the-counter drug brands. Our aim is to help manufacturers to improve their position in the market of self-medication. This market has very peculiar characteristics: consumers buy products in response to their specific health needs; nonetheless, the market is not strictly regulated in the same way that the prescription market, which allows firms to choose their pricing and communication strategies. Moreover, consumers are not forced by physicians to buy one specific drug, but they can choose the one they prefer. To develop our model we use the Analytic Network Process methodology, which allows integrating qualitative and quantitative judgments from many decision makers and deals with non-regular preference structures. The output of the model is a ranking of the brand value drivers, according to their importance in influencing the consumers purchase intentions. We find that advertising plays a major role in this setting. To test our model and validate our results, we analyse three Italian brands that produceover-the-counter (OTC) Diclofenac-based drugs. In addition, we compare our results with their market share.

Assessing perceived organizational leadership styles through twitter text mining

We propose a text classification tool based on support vector machines for the assessment of organizational leadership styles, as appearing to Twitter users. We collected Twitter data over 51 days, related to the first 30 Italian organizations in the 2015 ranking of Forbes Global 2000—out of which we selected the five with the most relevant volumes of tweets. We analyzed the communication of the company leaders, together with the dialogue among the stakeholders of each company, to understand the association with perceived leadership styles and dimensions. To assess leadership profiles, we referred to the 10‐factor model developed by Barchiesi and La Bella in 2007. We maintain the distinctiveness of the approach we propose, as it allows a rapid assessment of the perceived leadership capabilities of an enterprise, as they emerge from its social media interactions. It can also be used to show how companies respond and manage their communication when specific events take place, and to assess their stakeholders reactions.