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Introduction to the Minitrack on Reports from the Field: Knowledge and Learning Applications in Practice
Get PDFWelcome to this, the 53rd Hawaii International Conference on System Sciences (HICSS) conference. This Reports from the Field Minitrack, under the Knowledge Innovation and Entrepreneurial Systems Track, proudly brings you the latest research focused on the application of innovation of knowledge management issues as reported by both researchers and practitioners alike. With the focus on application, this minitrack helps practioners and theorists alike. It is here we examine how theory informs and impacts practice as well as how practice can influence theory from the practioner perspective
Planetary carambolage: The evolutionary political economy of technology, nature and work
Get PDFThe following editorial introduces the special issue (SI) on “Work, Environment and Planetary-scale Computation in Political-Economic Evolution”. Here, however, we go beyond an outline of what each contribution to the SI addresses, and attempt to draw a more pronounced shared embedding of the arguments that have come to the fore. The original idea of this SI was to synthesize a range of contemporary global political-economic challenges, i.e. (1) technology (esp. digital transformation), (2) nature (esp. ecological crisis) and (3) work (esp. precarization via the evolving platform economy). The main argument developed in this editorial reflection focuses on the common ground and origin of those processes found in the complex evolution of capitalist development. We frame the latter by assigning it a new term, i.e. “planetary carambolage”
City logistics: Towards a blockchain decision framework for collaborative parcel deliveries in micro-hubs
Get PDFThe growth in e-commerce has led to increased pressure within the courier, express and parcel (CEP) sector to tackle the ‘last-mile’ issue and come up with solutions that not only satisfy the customers, but also other stakeholders such as city councils and other regulatory bodies. Scholars have highlighted micro-hubs and the associated horizontal collaboration as a possible solution, which might help alleviate problems associated with last-mile logistics in inner-city centers. However, trust and data exchange issues are considerable barriers to the introduction of horizontal collaboration, in particular between CEP carriers. To address the lack of trust and the issue of data exchange between carriers, the use of blockchain technology may present a solution, but existing research so far is limited concerning frameworks that specifically discuss blockchain technology in the context of micro-hubs and last-mile deliveries. In response, this paper presents a blockchain decision framework for a horizontal collaboration between CEP carriers based on key characteristics of existing blockchain decision models and relevant related research in the area of logistics and last-mile distribution. This is the first study that specifically addresses the use of blockchain technology for horizontal collaboration in the context of micro-hubs and last-mile deliveries
A decade of Semantic Web research through the lenses of a mixed methods approach
Get PDFThe identification of research topics and trends is an important scientometric activity, as it can help guide the direction of future research. In the Semantic Web area, initially topic and trend detection was primarily performed through qualitative, top-down style approaches, that rely on expert knowledge. More recently, data-driven, bottom-up approaches have been proposed that offer a quantitative analysis of the evolution of a research domain. In this paper, we aim to provide a broader and more complete picture of Semantic Web topics and trends by adopting a mixed methods methodology, which allows for the combined use of both qualitative and quantitative approaches. Concretely, we build on a qualitative analysis of the main seminal papers, which adopt a top-down approach, and on quantitative results derived with three bottom-up data-driven approaches (Rexplore, Saffron, PoolParty), on a corpus of Semantic Web papers published between 2006 and 2015. In this process, we both use the latter for “fact-checking” on the former and also to derive key findings in relation to the strengths and weaknesses of top-down and bottom up approaches to research topic identification. Although we provide a detailed study on the past decade of Semantic Web research, the findings and the methodology are relevant not only for our community but beyond the area of the Semantic Web to other research fields as well
What we know about anticonsumption: An attempt to nail jelly to the wall
Get PDFDespite burgeoning academic interest in anticonsumption, a lack of definitional clarity
and overlapping constructs beleaguer the pertinent literature, preventing research in
the field from reaching its full potential. This paper aims to strengthen the foundations
for advancing knowledge in this fragmented field by (a) undertaking a thorough
systematic review of literature; (b) charting the scope of anticonsumption literature
based on network analysis and attempting to delineate overlapping areas; (c) providing
an integrated framework of anticonsumption research, including antecedents,
moderators, and consequences; and (d) suggesting a set of specific research
propositions that will enable the field to move forward. Toward these aims, we
analyzed 120 anticonsumption papers revealed in the literature review, identifying a
number of important anticonsumption‐related topics that warrant further investigation.
Moreover, we suggest a research framework which reveals antecedents, causal
sequences, and consequences of anticonsumption. Finally, a research agenda based on
this integrated framework indicates promising areas for future research
Economic Games as Estimators
Get PDFDiscrete event games are discrete time dynamical systems whose state transitions are discrete events caused by actions taken by agents within the game. The agents’ objectives and associated decision rules need not be known to the game designer in order to impose struc- ture on a game’s reachable states. Mechanism design for discrete event games is accomplished by declaring desirable invariant properties and restricting the state transition functions to conserve these properties at every point in time for all admissible actions and for all agents, using techniques familiar from state-feedback control theory. Building upon these connections to control theory, a framework is developed to equip these games with estimation properties of signals which are private to the agents playing the game. Token bonding curves are presented as discrete event games and numerical experiments are used to investigate their signal processing properties with a focus on input-output response dynamics.Series: Working Paper Series / Institute for Cryptoeconomics / Interdisciplinary Researc
Research note: an analytical perspective on market decisions and asymmetric cost behavior
Get PDFAsymmetric cost behavior has attracted the interest of many (empirical) researchers
in the last years. Prior research determines several sources of this behavior such as
resource adjustment costs, uncertainties and related beliefs, agency problems, and
fixed costs. Empirical studies measure firms’ cost behavior using total firm costs
and sales. In imperfect markets, firms react to changing market conditions by adapting
output prices and quantities so that both total firm costs and sales are affected.
However, changing output prices only directly affects sales and not costs. Based on
an economic model, we identify market decisions (output quantity and pricing decisions)
as an additional source of measured asymmetric cost behavior
On the design of R-based scalable frameworks for data science applications
Get PDFThis thesis is comprised of three papers "On the design of R-based scalable frameworks for data science applications". We discuss the design of conceptual and computational frameworks for the R language for statistical computing and graphics and build software artifacts for two typical data science use cases: optimization problem solving and large scale text analysis. Each part follows a design science approach. We use a verification method for the software frameworks introduced, i.e., prototypical instantiations of the designed artifacts are evaluated on the basis of real-world applications in mixed integer optimization (consensus journal ranking) and text mining (culturomics).
The first paper introduces an extensible object oriented R Optimization Infrastructure (ROI). Methods from the field of optimization play an important role in many techniques routinely used in statistics, machine learning and data science. Often, implementations of these methods rely on highly specialized optimization algorithms, designed to be only applicable within a specific application. However, in many instances recent advances, in particular in the field of convex optimization, make it possible to conveniently and straightforwardly use modern solvers instead with the advantage of enabling broader usage scenarios and thus promoting reusability. With ROI one can formulate and solve optimization problems in a consistent way. It is capable of modeling linear, quadratic, conic, and general nonlinear optimization problems. Furthermore, the paper discusses how extension packages can add additional optimization solvers, read/write functions and additional resources such as model collections. Selected examples from the field of statistics conclude the paper.
With the second paper we aim to answer two questions. Firstly, it addresses the issue on how to construct suitable aggregates of individual journal rankings, using an optimization-based consensus ranking approach. Secondly, the presented application serves as an evaluation of the ROI prototype. Regarding the first research question we apply the proposed method to a subset of marketing-related journals from a list of collected journal rankings. Next, the paper studies the stability of the derived consensus solution, and degeneration effects that occur when excluding journals and/or rankings. Finally, we investigate the similarities/dissimilarities of the consensus with a naive meta-ranking and with individual rankings. The results show that, even though journals are not uniformly ranked, one may derive a consensus ranking with considerably high agreement with the individual rankings.
In the third paper we examine how we can extend the text mining package tm to handle large (text) corpora. This enables statisticians to answer many interesting research questions via statistical analysis or modeling of data sets that cannot be analyzed easily otherwise, e.g., due to software or hardware induced data size limitations. Adequate programming models like MapReduce facilitate parallelization of text mining tasks and allow for processing large data sets by using a distributed file system possibly spanning over several machines, e.g., in a cluster of workstations. The paper presents a plug-in package to tm called tm.plugin.dc implementing a distributed corpus class which can take advantage of the Hadoop MapReduce library for large scale text mining tasks. We evaluate the presented prototype on the basis of an application in culturomics and show that it can handle data sets of significant size efficiently
Comparing Travel Time Estimates of Routing Applications in Vienna.
Get PDFHow are travel times displayed by different navigation apps? Do the way in which these work differ for
different modes of transportation? We found unexpected divergence in the way travel time is displayed
both between apps and within apps, when conducting testing on travel routing apps in Vienna. As a result,
this paper will provide a brief overview of how travel times are displayed by commonly used apps in
Vienna and how these differ. In conclusion, we will suggest different avenues for additional research based
on these findings and illustrate the challenges of user accountability associated with these apps
Boon or curse? A contingent view on the relationship between strategic planning and organizational ambidexterity
Get PDFNumerous scholars have attempted to explain which factors allow for organizational ambidexterity. Strategic planning, as a possible antecedent, has not been considered so far. This is surprising because strategic planning is among the most widely used strategic decision-making tools in management practice and one of the most extensively studied concepts in management research. In addition, prior research has demonstrated the potential of strategic planning to impact innovation-related outcomes—both positively and negatively. Here, we investigate the association between strategic planning and organizational ambidexterity using a survey of 217 senior executives. We highlight the importance of considering how executives use strategic planning. Our results support the hypothesis that strategic planning's positive or negative association with organizational ambidexterity is contingent on other organizational factors. Our findings reveal that strategic planning is only positively associated with organizational ambidexterity when leaders' innovation orientation is extraordinarily high. We further contextualize this interaction effect by considering the environmental uncertainty perceived by the top management. This work contributes to the literature by examining the antecedents of organizational ambidexterity