What are the roles of software product managers? An empirical investigation

Software product management covers both technical and business activities to management of products like roadmaps, strategic, tactical, and release planning. In practice, one product manager is seldom responsible for all these activities but several persons share the responsibilities. Therefore, it is important to understand the boundaries of product managers’ work in managing software products, as well as the impact a product manager has on the company business. The purpose of the study is to clarify what roles of software product managers exist and understand how these roles are interrelated with each other and the whole structure and business of an organization. The study is designed as an interpretative qualitative study using grounded theory as the research method. Based on the gathered data we developed a framework that reveals the role of a product manager in the organization and shows how this role can evolve by extending the level of responsibilities. Using the framework, we identified four stereotypical roles of product managers in the studied organizations: experts, strategists, leaders, and problem solvers. The presented framework shows that product managers’ roles are not limited to the conception of the “mini-CEO.” The results allow product managers and top management to collaborate effectively by assigning responsibilities and managing expectations by having a common tool for understanding the role of product managers in the organization.     

What drives continued knowledge sharing? An investigation of knowledge-contribution and -seeking beliefs

Knowledge management (KM) research has yielded extensive explanations regarding the individual's motivation to share knowledge, each with different sets of factors. Yet the study of continued knowledge sharing is rare. There has been little research investigating this issue from contributing and seeking perspectives—the two distinct, but closely interrelated, facets of continued knowledge sharing. We propose that knowledge management system (KMS) users' beliefs are contextually differentiated, and thus a distinction between knowledge-contribution and knowledge-seeking behaviors and an adequate emphasis on their variance in terms of user belief is needed. By incorporating the knowledge-contribution and knowledge-seeking perspectives in a single study, we model and examine the differences among driving factors in two behavioral contexts, provide the conceptual comparisons and preliminary discussions, and thus advance our understanding of continued knowledge sharing via the KMS.     

What should developers be aware of? An empirical study on the directives of API documentation

Application Programming Interfaces (API) are exposed to developers in order to reuse software libraries. API directives are natural-language statements in API documentation that make developers aware of constraints and guidelines related to the usage of an API. This paper presents the design and the results of an empirical study on the directives of API documentation of object-oriented libraries. Its main contribution is to propose and extensively discuss a taxonomy of 23 kinds of API directives.     

Older adults’ use of smart phones: an investigation of the factors influencing the acceptance of new functions

After adopting mobile phones, most older adults use them only for calling and SMS. The purpose of this study is to extend their usage of mobile phones to new functions. To understand older adults’ requirements of mobile phones, a questionnaire was constructed and 351 Chinese older adults were recruited to complete the questionnaires. Data collected through the questionnaires were analysed using explorative factor analysis. The results revealed that older adults’ requirements were composed of 10 factors: Find a Specific Function, Awareness and Attractiveness, Readability, Personal Concern, Soft Keys and Multi-tap, Hardware Capacity, Touch Screen, Concern of Learning, Connectivity, and Social Influence. Then, from the above 10 factors, the 6 most important factors were revealed using multiple linear regression analysis. The results imply that accepting new functions is different from accepting a product. Readability and Find a Specific Function, which are critical for older adults’ acceptance of feature phones, are not determinants of their acceptance of new functions in smart phones.     

What makes the difference? An empirical comparison of fusion strategies for multimodal language analysis

Multimodal video sentiment analysis is a rapidly growing area. It combines verbal (i.e., linguistic) and non-verbal modalities (i.e., visual, acoustic) to predict the sentiment of utterances. A recent trend has been geared towards different modality fusion models utilizing various attention, memory and recurrent components. However, there lacks a systematic investigation on how these different components contribute to solving the problem as well as their limitations. This paper aims to fill the gap, marking the following key innovations. We present the first large-scale and comprehensive empirical comparison of eleven state-of-the-art (SOTA) modality fusion approaches in two video sentiment analysis tasks, with three SOTA benchmark corpora. An in-depth analysis of the results shows that the attention mechanisms are the most effective for modelling crossmodal interactions, yet they are computationally expensive. Second, additional levels of crossmodal interaction decrease performance. Third, positive sentiment utterances are the most challenging cases for all approaches. Finally, integrating context and utilizing the linguistic modality as a pivot for non-verbal modalities improve performance. We expect that the findings would provide helpful insights and guidance to the development of more effective modality fusion models.     

Are large C++ classes change-prone? An empirical investigation

It is crucial, but hard, to predict the parts of a system that must be changed in the next release of a software system. Previous results showed that professional and experienced developers largely underpredict the number of software entities subject to change in the next release, even though a thorough impact analysis driven by requirements is conducted. Thus, there is a strong need for understanding what kind of properties of a system make it more or less vulnerable to change. This empirical study analyzes change of C++ source code classes that occurred in two releases of the industrial object-oriented project PMR (Performance Management Traffic Recording). PMR is a part of the operation and support system of a cellular telecom system. The result, which is consistent over the two releases despite different kinds of new requirements, shows that the median size in the set of changed classes is significantly larger than in the set of unchanged classes. Our interpretation of the results is that large classes are more change-prone than small classes, and that large classes therefore always should be regarded as candidates for change. © 1998 John Wiley & Sons, Ltd.     

What do web users do? An empirical analysis of web use

This paper provides an empirical characterization of user actions at the web browser. The study is based on an analysis of 4 months of logged client-side data that describes user actions with recent versions of Netscape Navigator. In particular, the logged data allow us to determine the title, URL and time of each page visit, how often they visited each page, how long they spent at each page, the growth and content of bookmark collections, as well as a variety of other aspects of user interaction with the web. The results update and extend prior empirical characterizations of web use. Among the results we show that web page revisitation is a much more prevalent activity than previously reported (approximately 81% of pages have been previously visited by the user), that most pages are visited for a surprisingly short period of time, that users maintain large (and possibly overwhelming) bookmark collections, and that there is a marked lack of commonality in the pages visited by different users. These results have implications for a wide range of web-based tools including the interface features provided by web browsers, the design of caching proxy servers, and the design of efficient web sites.     

What drives the sales of paid knowledge products? A two-phase approach

Knowledge-sharing services in virtual communities have enjoyed tremendous growth in recent years. These communities enable content creators (i.e., speakers) to share knowledge by broadcasting “lives” to which audiences can pay to listen. Our study explores the key antecedents of the sales of paid knowledge products. Data were obtained from the Zhihu Live community to verify the hypotheses. On the Zhihu Live platform, knowledge products are provided in the form of audio broadcasts. A potential listener can choose to purchase a live either before (phase 1) or after (phase 2) it is broadcasted. Accordingly, this study proposes a two-phase approach to investigate the effects of key factors that affect the sales of lives in each phase. Our results suggest that price negatively affects a live’s sales and cumulative prior sales positively affect next-day sales in both phases. Furthermore, review score and speaker–audience interactions have significant effects on sales after a live is broadcasted. The contributions and implications of the results are discussed.     

How do monetary incentives influence giving? An empirical investigation of matching subsidies on kiva

Information Systems and e-Business Management - Matching subsidies, through which third-party institutions provide a dollar-for-dollar match of private contributions made through selected...     

Multi-dimensional students’ evaluation of e-learning systems in the higher education context: An empirical investigation

There has been little research on assessment of learning management systems (LMS) within educational organizations as both a web-based learning system for e-learning and as a supportive tool for blended learning environments. This study proposes a conceptual e-learning assessment model, hexagonal e-learning assessment model (HELAM) suggesting a multi-dimensional approach for LMS evaluation via six dimensions: (1) system quality, (2) service quality, (3) content quality, (4) learner perspective, (5) instructor attitudes, and (6) supportive issues. A survey instrument based on HELAM has been developed and applied to 84 learners. This sample consists of students at both undergraduate and graduate levels who are users of a web-based learning management system, U-Link, at Brunel University, UK. The survey instrument has been tested for content validity, reliability, and criterion-based predictive validity. The analytical results strongly support the appropriateness of the proposed model in evaluating LMSs through learners’ satisfaction. The explanatory factor analysis showed that each of the six dimensions of the proposed model had a significant effect on the learners’ perceived satisfaction. Findings of this research will be valuable for both academics and practitioners of e-learning systems.     

What are features? An ontology-based review of the literature

Feature-based product modeling is the leading approach for the integrated representation of engineering product data. On the one side, this approach has stimulated the development of formal models and vocabularies, data standards and computational ontologies. On the other side, the current ways to model features are considered problematic since it lacks a principled and uniform methodology for feature representation.This paper reviews the state of art of feature-based modeling approaches by concentrating on how features are conceptualized. It points out the drawbacks of current approaches and proposes a high-level ontology-based perspective to harmonize the definition of feature.     

Parameter tuning or default values? An empirical investigation in search-based software engineering

Many software engineering problems have been addressed with search algorithms. Search algorithms usually depend on several parameters (e.g., population size and crossover rate in genetic algorithms), and the choice of these parameters can have an impact on the performance of the algorithm. It has been formally proven in the No Free Lunch theorem that it is impossible to tune a search algorithm such that it will have optimal settings for all possible problems. So, how to properly set the parameters of a search algorithm for a given software engineering problem? In this paper, we carry out the largest empirical analysis so far on parameter tuning in search-based software engineering. More than one million experiments were carried out and statistically analyzed in the context of test data generation for object-oriented software using the EvoSuite tool. Results show that tuning does indeed have impact on the performance of a search algorithm. But, at least in the context of test data generation, it does not seem easy to find good settings that significantly outperform the “default” values suggested in the literature. This has very practical value for both researchers (e.g., when different techniques are compared) and practitioners. Using “default” values is a reasonable and justified choice, whereas parameter tuning is a long and expensive process that might or might not pay off in the end.     

An empirical examination of factors affecting college students’ proactive stickiness with a web-based English learning environment

Drawing on the Social Cognitive Theory (SCT) and Uses and Gratifications (U&G) theory, this study develops a conceptual model to investigate the determinants of college students’ proactive “stickiness” with a web-based English learning (WBEL) environment. The model was validated using a cross-sectional survey of 306 college students. The partial least squares (PLS) method was applied to validate the measurement properties and proposed hypotheses. Overall, the empirical results show that computer self-efficacy, system characteristics, digital material features, interaction, learning outcome expectations and learning climate are critical affecting factors in determining student learning gratifications with WBEL, which is crucial to a college student’s proactive stickiness with the WBEL system. This study demonstrates the value in integrating findings from cognitive science and mass communication research to understand the WBEL processes involved. The findings provide initial insights into those factors that are likely critical antecedents for promoting college students’ English learning effectiveness through web-based technologies.     

Successful product or successful system? User satisfaction measurement of ERP software

Most software projects are largely undertaken with a focus on developing successful products rather than successful systems. For example, enterprise resource planning (ERP) products are generally developed in isolation from other system components like people, information or existing business processes. This paper applies the human-centred approach in studying the design of SAP-ERP system and measuring its user satisfaction. The objective of the paper is to explore the relationship between the human-centred dimensions (process, syntactic, semantic, social and pragmatic) and the user satisfaction on SAP-ERP system. This paper attempts to answer two questions: what human-centred model can provide a systematic and successful ERP system? And what methodology can be used for validating this model and how can it be applied for evaluating user satisfaction? The contributions of the paper are to address the need for the human-centred approach as a basis for the design of ERP system, to define a systematic human-centred model for measurement towards user satisfaction. This paper suggests the application of a proposed five dimensional model in measuring the human-centredness of SAP-ERP system and embarks a case study to conduct quantitative analysis. In conclusion the paper suggests an urgent and immediate need to develop scientific and engineering methodologies for designing, building, and analysing complex systems that centre on fundamental forms of human activity, supported by computer and communication technology.     

Ignorance is bliss? An empirical analysis of the determinants of PSS usefulness in practice

Planning support systems (PSS) enabled by smart city technologies (big data and information and communication technologies (ICTs)) are becoming more widespread in their availability, but have not yet been fully recognized as being useful in planning practice. Thus, a better understanding of the determinants of PSS usefulness in practice helps to improve the functional support of PSS for smart cities. This study is based on a recent international questionnaire (268 respondents) designed to evaluate the perceptions of scholars and practitioners in the smart city planning field. Based on the empirical evidence, this paper recommends that it is imperative for PSS developers and users to be more responsive to the fit for task-technology and user-technology (i.e., utility and usability, respectively) since they positively contribute to PSS usefulness in practice and to be more sensitive to the potential negative effects of contextual factors on PSS usefulness in smart cities. The empirical analyses further suggest that rather than merely striving for integrating smart city technologies into advancing PSS, the way that innovative PSS are integrated into the planning framework (i.e., how well PSS can satisfy the needs of planning tasks and users by considering context-specificities) is of great significance in promoting PSS's actual usefulness.     

What else do college students “do” while studying? An investigation of multitasking

We investigated the frequency and duration of distractions and media multitasking among college students engaged in a 3-h solitary study/homework session. Participant distractions were assessed with three different kinds of apparatus with increasing levels of potential intrusiveness: remote surveillance cameras, a head-mounted point-of-view video camera, and a mobile eyetracker. No evidence was obtained to indicate that method of assessment impacted multitasking behaviors. On average, students spent 73 min of the session listening to music while studying. In addition, students engaged with an average of 35 distractions of 6 s or longer over the course of 3 h, with an aggregated mean duration of 25 min. Higher homework task motivation and self-efficacy to concentrate on homework were associated with less frequent and shorter duration multitasking behaviors, while greater negative affect was linked to longer duration multitasking behaviors during the session. We discuss the implications of these data for assessment and for understanding the nature of distractions and media multitasking during solitary studying.     

What does it mean to be good at using a mobile device? An investigation of three levels of experience and skill

An increasing number of computer users lack formal training in operating their devices. These daily users cannot be described as novices or experts within the predominant view of expertise. In order to describe and better understand this type of self-taught intermediate level of skill, 10 casual users of a high-end smartphone series were compared to 10 novices and 4 professionals (help desk personnel) in their learning histories, task performance, and cognitive outcomes. Our study suggests that this type of self-taught intermediate level of skill is device-specific. Experienced users (casual users and experts) exhibited superior performance for representative tasks. This is mainly attributable to faster navigation and better knowledge of interface terminology, not to deeper conceptual representation of the problems. Interviews suggest that this skill is the consequence of routine use and three recurring learning events: familiarization, following of media, and ad hoc problem-solving situations. We conclude by discussing why intermediate levels of skill deserve more attention in HCI research.     

An empirical investigation linking learners’ adoption of blended learning to their intention of full e-learning

Learning management system (LMS) is playing a major role in higher academic institutions worldwide. Even though full e-learning is becoming a feasible strategy for a number of institutions in the world, some institutions, especially those in developing countries, are resisting a full e-learning environment. Consequently, these academic institutions initially adopt LMS for blended learning to assess their readiness for full e-learning transformation. There are a number of studies that investigate the determinants of full e-learning, but very limited studies investigate the link between learners’ perception of blended learning and full e-learning. The objective of this study was to link learners’ adoption (perceived ease of use, perceived usefulness (PU) and satisfaction) of LMS in blended learning and their personal characteristics (self-efficacy, technology experience and personal innovativeness) to their intention to use full e-learning. Data were collected through a questionnaire from 512 learners in Oman. The study found that personal innovativeness, PU and satisfaction of LMS in blended learning are significant to learners’ intention to engage in full e-learning. Thus, learners’ adoption of LMS in blended learning boosts their intention to full e-learning. The results provide useful insights for practitioners and researchers on full e-learning planning and strategy.