An integrated algorithm for three-way compositional data

Quality & Quantity - Compositional data with a tridimensional structure are not uncommon in social sciences. The CANDECOMP/PARAFAC model is one of the most adequate techniques for modeling...     

Taking a Second Look in a Warped Crystal Ball: Explaining the Accuracy of Revised Forecasts

The fundamental questions we address are whether firms with a higher initial forecasting ability are able to accurately revise the exit forecasts of their investments; and how co‐investment partners and value‐adding commitment with their investment influence the main effect. We explore these questions with novel and unique data collected via mixed research methods on venture capital firms’ forecasts of 114 portfolio companies. We find that venture capital firms that are better at making initial forecasts are less effective in revising their forecasts. In addition, while the number of co‐investment partners positively moderate this relationship, venture capital firms’ value‐adding commitment moderates it negatively. Our findings contribute to the literature on organizational forecasting as well as inter‐organizational knowledge transfer and knowledge creation. They also provide novel insights into venture capital literature and practice.     

New insights into venture capitalists' activity: IPO and time-to-exit forecast as antecedents of their post-investment involvement

We examine how VCFs' forecast of an IPO exit affects their breadth of advising and the likelihood of founder–CEO replacement shortly after they invest in a new venture. Moreover, we examine how the expected time-to-exit moderates these relationships. Our findings show that the likelihood of founder–CEO replacement upon receiving venture capital funding is significantly greater if a VCF perceives this company as a potential IPO as opposed to a trade sale, and this likelihood increases if the forecasted time-to-exit is short. We also illustrate how the breadth of advice varies as a function of the forecasted IPO and time-to-exit.     

Coherent Modeling and Forecasting of Mortality Patterns for Subpopulations Using Multiway Analysis of Compositions: An Application to Canadian Provinces and Territories

Mortality levels for subpopulations, such as countries in a region or provinces within a country, generally change in a similar fashion over time, as a result of common historical experiences in terms of health, culture, and economics. Forecasting mortality for such populations should consider the correlation between their mortality levels. In this perspective, we suggest using multilinear component techniques to identify a common time trend and then use it to forecast coherently the mortality of subpopulations. Moreover, this multiway approach is performed on life table deaths by referring to Compositional Data Analysis (CoDa) methodology. Compositional data are strictly positive values summing to a constant and represent part of a whole. Life table deaths are compositional by definition because they provide the age composition of deaths per year and sum to the life table radix. In bilinear models the use of life table deaths treated as compositions generally leads to less biased forecasts than other commonly used models by not assuming a constant rate of mortality improvement. As a consequence, an extension of this approach to multiway data is here presented. Specifically, a CoDa adaptation of the Tucker3 model is implemented for life table deaths arranged in three-dimensional arrays indexed by time, age, and population. The proposed procedure is used to forecast the mortality of Canadian provinces in a comparative study. The results show that the proposed model leads to coherent forecasts.     

The state of #digitalentrepreneurship: a big data Leximancer analysis of social media activity

This paper examined online sentiment, key themes and patterns evident in social media activity about digital entrepreneurship. It provides a snapshot-in-time, visual-first perspective on social media user-generated-content (UGC) to better understand the topic of digital entrepreneurship. Global data consisting of 31,017 publicly available UGC which used the #digitalentrepreneurship (hashtag) and the keywords ‘digital entrepreneurship’ were collected. A computer assisted qualitative data analysis software (CAQDAS), Leximancer, was used for an automated text-mining analysis. There is positive online sentiment surrounding digital entrepreneurship technology, ecosystem and industry, and one which promotes women transformation of digital entrepreneurship globally. Negative sentiment pointed out that future development and support of youth in digital entrepreneurship is needed. Digital entrepreneurs were identified as needing to focus on strategy, leadership, management, and social media platforms. A comprehensive perspective on the state of digital entrepreneurship in online UGC is provided. Insights into the challenges, issues, changes, success stories and key topics in digital entrepreneurship are highlighted. Future research is encouraged to adopt longitudinal and quantitative approaches, to provide further insights into the evolution of digital entrepreneurship. The paper contributes to the entrepreneurship literature by applying the Social Exchange Theory and the Social Media User Engagement Framework to better understand social media activity around digital entrepreneurship. The findings show that there are real challenges and issues to overcome but there are also changes occurring in digital entrepreneurship and social media users are keen to share and learn from digital entrepreneurship success stories.

     

On truncated bivariate discrete distributions: A unified treatment

A unified treatment of three types of zero class truncation for bivariate discrete distributions is presented. Using the probability generating function approach, various properties of the truncated distributions are examined in association with the corresponding properties of the initial complete form of the distribution. Expressions for moments and conditional distributions are also obtained. Bivariate versions of the Thomas and the Intervened Poisson distributions are introduced and used as illustrative examples. Received November 2000/Revised March 2002     

Best friend or broken tool? Exploring the co-existence of humans and artificial intelligence in the workplace ecosystem

Artificial intelligence (AI) has become an important topic in business literature and strategy talk. Yet, much of this literature is normative and conceptual in nature. How organizational members perceive AI and the job role changes that come with it is, so far, largely unknown territory for both HR scholars and practitioners. We sought to investigate the relationship between humans and AI and conducted an in-depth exploratory study into the co-existence of humans and two early-stage AI-solutions, one for “low-status” automation and another for “high-status”; augmentation. We suggest that different organizational groups may engage in distinctly different sensemaking processes regarding AI, an important insight for successful HRM strategies when AI is being introduced into the workplace. Moreover, contrary to recent conceptual work, our findings indicate that AI-enabled automation and augmentation solutions may not be detached from nor exist in tension with each other. They are deeply embedded in organizational processes and workflows for which people who co-exist with the technologies must take ownership. Our findings, in part, go against discussions on AI “taking over” jobs or deskilling humans. We describe a more nuanced version of reality fluctuating around the various ways different organizational groups encounter different AI-solutions in their daily work. Finally, our study warns against unconditional technological enthusiasm, managerial ignorance of the nature of work that employees undertake in different organizational groups, and a neglect of the time and effort required to successfully implement AI-solutions that affect not only the home organization but also members of the broader ecosystem.