title: An empirical investigation into music listening behaviour in the presence of the network effect

authors: Ghaffari, Mona

subjects: Network effect

abstract: The rapid expansion of online platforms has revolutionised the digital media industry, transforming the way people consume digital content and interact with each other and the platforms. The network effects (NEs) play a vital role in the success of online platforms, fostering user collaboration and interest exchange, thereby creating a positive feedback loop that influences user behaviours and contributes to a platform’s success. However, initial studies exploring the NEs phenomenon primarily focused on network size, predating the widespread adoption of online platforms, and thus providing little insight into the application of NEs in the online platform context. Furthermore, despite extensive studies on online platforms, established theoretical constructs and practical frameworks that integrate other variables contributing to NEs in online platforms are lacking.
The thesis consists of three research chapters that significantly contribute to the study of NEs and their influence on users’ online music listening behaviours. In the first study, a systematic and rigorous approach was adopted to develop an NEs measurement scale. Drawing on social network and social action theories, we developed a novel NEs model with two subconstructs: social network structure and social action. An empirical research design was applied using the data of 200 Last.fm users. We employed a combination of partial least squares (PLS) path modelling and an expert focus group to validate the model. The results supported the validity and reliability of the developed NEs model.
The second study addressed the scarcity of longitudinal analysis related to the evolving nature of NEs and the lack of empirical research to measure the impact of NEs on online music listening behaviours. We examined the NEs construct from our first study to show the impact of NEs on Last.fm users’ music listening behaviours cross-sectionally and longitudinally. The research method used was partial least square-structural equation modelling (PLS-SEM) of data obtained from Last.fm within two time intervals, targeting 1,708 users. Our study found that NEs positively influence users’ music listening behaviours, including the quantity, variety, and novelty of their music consumption. Specifically, the multigroup analysis revealed that the positive impact of NEs on users’ music listening behaviours becomes stronger over time. Furthermore, as the social network structure strengthens and users engage in more social actions, there is a carryover effect on NEs at subsequent times.
The third study explored the impact of COVID-19 on online music listening behaviours in relation to listeners’ social interactions. We analysed the online music listening behaviours and social interactions of 37,328 Last.fm users in 45 countries before and after the first wave of confinement, using robust causal inference methods: difference in differences (DiD) and two-way fixed effects (TWFE). The results revealed that, in response to COVID-19, there was a decline in the quantity, variety, and novelty of music consumption, with a shift towards mainstream artists. However, our analysis also found that users with more online social connections and communications exhibited the opposite behaviour. This study provides guidance for the development of innovative design strategies for digital media, including music, movies, and games.

text: An empirical investigation into music listening behaviour in the presence of the network effect The rapid expansion of online platforms has revolutionised the digital media industry, transforming the way people consume digital content and interact with each other and the platforms. The network effects (NEs) play a vital role in the success of online platforms, fostering user collaboration and interest exchange, thereby creating a positive feedback loop that influences user behaviours and contributes to a platform’s success. However, initial studies exploring the NEs phenomenon primarily focused on network size, predating the widespread adoption of online platforms, and thus providing little insight into the application of NEs in the online platform context. Furthermore, despite extensive studies on online platforms, established theoretical constructs and practical frameworks that integrate other variables contributing to NEs in online platforms are lacking.
The thesis consists of three research chapters that significantly contribute to the study of NEs and their influence on users’ online music listening behaviours. In the first study, a systematic and rigorous approach was adopted to develop an NEs measurement scale. Drawing on social network and social action theories, we developed a novel NEs model with two subconstructs: social network structure and social action. An empirical research design was applied using the data of 200 Last.fm users. We employed a combination of partial least squares (PLS) path modelling and an expert focus group to validate the model. The results supported the validity and reliability of the developed NEs model.
The second study addressed the scarcity of longitudinal analysis related to the evolving nature of NEs and the lack of empirical research to measure the impact of NEs on online music listening behaviours. We examined the NEs construct from our first study to show the impact of NEs on Last.fm users’ music listening behaviours cross-sectionally and longitudinally. The research method used was partial least square-structural equation modelling (PLS-SEM) of data obtained from Last.fm within two time intervals, targeting 1,708 users. Our study found that NEs positively influence users’ music listening behaviours, including the quantity, variety, and novelty of their music consumption. Specifically, the multigroup analysis revealed that the positive impact of NEs on users’ music listening behaviours becomes stronger over time. Furthermore, as the social network structure strengthens and users engage in more social actions, there is a carryover effect on NEs at subsequent times.
The third study explored the impact of COVID-19 on online music listening behaviours in relation to listeners’ social interactions. We analysed the online music listening behaviours and social interactions of 37,328 Last.fm users in 45 countries before and after the first wave of confinement, using robust causal inference methods: difference in differences (DiD) and two-way fixed effects (TWFE). The results revealed that, in response to COVID-19, there was a decline in the quantity, variety, and novelty of music consumption, with a shift towards mainstream artists. However, our analysis also found that users with more online social connections and communications exhibited the opposite behaviour. This study provides guidance for the development of innovative design strategies for digital media, including music, movies, and games.

year: 2023

title: Portfolio structure and optimisation of momentum returns

authors: Gupta, Kartick

subjects: momentum returns

abstract: This study analyses momentum returns in 54 countries covering 34 years.  It is the first study where optimising programmes are applied to momentum returns and portfolio selection.  Momentum returns have remained a contentious topic and a substantial amount of research purports to support and negate this anomaly.  Momentum studies have previously concentrated on finding the cause of this anomaly or determining whether abnormal returns are present only in a particular dataset.  However, there is no clear consensus regarding how to construct/implement a momentum strategy.  To date it has been unclear as to how many portfolios should be created, whether or not the portfolios should be equally-weighted or value-weighted and how the momentum returns will change when a chosen strategy is constructed/implemented compared to an alternative strategy.  This lack of precision concerning how to construct/implement momentum strategy potentially leads to confounding results.  This current thesis contributes to an understanding of the  structure impact effect  by computing momentum returns for changing portfolio structures and observing the magnitude of the impact on returns on a specially crafted database of 52,593 stocks from 54 countries over the time period 1973-2007.
The two important empirical extensions are the industrial momentum and the 52-week high momentum models.  Both the industrial momentum and 52-week high momentum strategies claim that their returns are superior to the traditional momentum return and possess superior explanatory power.  Empirical evidence, to date, has not been available to attest to whether the results hold true when applied in different markets.  This gap in knowledge motivated this research investigation of multiple countries addressing how different methods of calculating returns, different approaches to momentum strategy, different portfolio weighting process impact upon the robustness of results.
This research also addresses the question of whether momentum returns can be increased through the use of optimisation algorithms.  Traditionally, little attention has been paid to the portfolio weighting with either an equal-weighted or value-weighted approach to allocating funds to the Winner and Loser portfolios.  This study proposes an alternative way of allocating money to the Winner and Loser portfolios with the goal of generating increased returns.  Eight different algorithms are applied to the share returns to determine whether one method is clearly superior to others in maximising the momentum returns for the synthesised portfolios over a period of time.  This is the first study of its type where optimising programmes are applied to momentum returns and portfolio selection and covers several countries.
The results indicate that momentum returns are robust on a global scale and the returns are by and large statistically significant under different portfolio construction approaches.  Both the industrial and 52-week momentum strategies remain positive and statistically significant but do not generate the same magnitude of returns as the conventional momentum return model.  The optimisation of momentum return shows promising results as a number of optimisation techniques do enhance momentum returns.    As the potential to increase returns becomes known, traders will quickly react and there is likely to be a range of new investment products arising.

text: Portfolio structure and optimisation of momentum returns This study analyses momentum returns in 54 countries covering 34 years.  It is the first study where optimising programmes are applied to momentum returns and portfolio selection.  Momentum returns have remained a contentious topic and a substantial amount of research purports to support and negate this anomaly.  Momentum studies have previously concentrated on finding the cause of this anomaly or determining whether abnormal returns are present only in a particular dataset.  However, there is no clear consensus regarding how to construct/implement a momentum strategy.  To date it has been unclear as to how many portfolios should be created, whether or not the portfolios should be equally-weighted or value-weighted and how the momentum returns will change when a chosen strategy is constructed/implemented compared to an alternative strategy.  This lack of precision concerning how to construct/implement momentum strategy potentially leads to confounding results.  This current thesis contributes to an understanding of the  structure impact effect  by computing momentum returns for changing portfolio structures and observing the magnitude of the impact on returns on a specially crafted database of 52,593 stocks from 54 countries over the time period 1973-2007.
The two important empirical extensions are the industrial momentum and the 52-week high momentum models.  Both the industrial momentum and 52-week high momentum strategies claim that their returns are superior to the traditional momentum return and possess superior explanatory power.  Empirical evidence, to date, has not been available to attest to whether the results hold true when applied in different markets.  This gap in knowledge motivated this research investigation of multiple countries addressing how different methods of calculating returns, different approaches to momentum strategy, different portfolio weighting process impact upon the robustness of results.
This research also addresses the question of whether momentum returns can be increased through the use of optimisation algorithms.  Traditionally, little attention has been paid to the portfolio weighting with either an equal-weighted or value-weighted approach to allocating funds to the Winner and Loser portfolios.  This study proposes an alternative way of allocating money to the Winner and Loser portfolios with the goal of generating increased returns.  Eight different algorithms are applied to the share returns to determine whether one method is clearly superior to others in maximising the momentum returns for the synthesised portfolios over a period of time.  This is the first study of its type where optimising programmes are applied to momentum returns and portfolio selection and covers several countries.
The results indicate that momentum returns are robust on a global scale and the returns are by and large statistically significant under different portfolio construction approaches.  Both the industrial and 52-week momentum strategies remain positive and statistically significant but do not generate the same magnitude of returns as the conventional momentum return model.  The optimisation of momentum return shows promising results as a number of optimisation techniques do enhance momentum returns.    As the potential to increase returns becomes known, traders will quickly react and there is likely to be a range of new investment products arising.

year: 2010

title: Weaving the mat of Māori and Pacific learner success

authors: Tiakiwai, Sarah-Jane

subjects: Supporting learners, Pacific learner success, Māori learner success, higher education

abstract: The mat we are trying to weave at the University of Waikato to address educational outcomes, disparities and inequities in education for Māori and Pacific learners will weave rich data, stories and experience. Our goal is to use data to be better informed about what works for Māori and Pacific learners and what does not. Data is useful in building a more complete picture of what is happening to students, but student voice and previous research that has already captured the voices of Māori and Pacific experts, educators, students, families and communities can tell us more about why we are getting these outcomes. As we harness data to improve our knowledge, we must not forget the stories already in the mat and the stories being woven in the mat, for the stories are the gold.

This report details our work on this data-informed rather than data-driven project. It discusses how improved data and data analytic capability enhanced our understanding of the literature on Māori and Pacific learner success and the experience of Māori and Pacific learners at UoW. Our research and the report, however, also unapologetically privilege case studies through literature and Māori and Pacific student voices. We lay out the various materials – data, literature and voice – that will form our mat with this in mind, weaving them together in order to achieve better outcomes for Māori and Pacific learners at our university. These learners are the why of this mahi. Their success will create a beautiful pattern in the
weave.

text: Weaving the mat of Māori and Pacific learner success The mat we are trying to weave at the University of Waikato to address educational outcomes, disparities and inequities in education for Māori and Pacific learners will weave rich data, stories and experience. Our goal is to use data to be better informed about what works for Māori and Pacific learners and what does not. Data is useful in building a more complete picture of what is happening to students, but student voice and previous research that has already captured the voices of Māori and Pacific experts, educators, students, families and communities can tell us more about why we are getting these outcomes. As we harness data to improve our knowledge, we must not forget the stories already in the mat and the stories being woven in the mat, for the stories are the gold.

This report details our work on this data-informed rather than data-driven project. It discusses how improved data and data analytic capability enhanced our understanding of the literature on Māori and Pacific learner success and the experience of Māori and Pacific learners at UoW. Our research and the report, however, also unapologetically privilege case studies through literature and Māori and Pacific student voices. We lay out the various materials – data, literature and voice – that will form our mat with this in mind, weaving them together in order to achieve better outcomes for Māori and Pacific learners at our university. These learners are the why of this mahi. Their success will create a beautiful pattern in the
weave.

year: 2022-06