Theory-Guided Modeling and Empiricism in Information Systems Research

The study of scientific collaboration through network analysis can give interesting conclusions about the publication habits of a scientific community. Co-authorship networks represent scientific collaboration as a graph: nodes correspond to authors, edges between nodes mark joint publications (Newman 2001a,b). Scientific publishing is decentralized. Choices of co-authors and research topics are seldomly globally coordinated. Still, the structure of co-authorship networks is far from random. Co-authorship networks are governed by principles that are similar in other complex networks such as social networks (Wasserman and Faust 1994), networks of citations between scientific papers (Egghe and Rousseau 1990), the World Wide Web (Albert and Barabási 1999, Kleinberg et al. 1999) or power grids (Watts and Strogatz 1998). It is therefore not astounding that scholars have studied co-authorship networks in considerable detail and in a variety of contexts, such as physics (Newman 2001a), evolutionary computation (Cotta and Merelo 2007) or computer supported cooperative work (Horn et al. 2004).

In the software industry, as well as in numerous other IT industries, products are often offered as systems consisting of complementary components (Gawer and Henderson 2007). In this context, specific components take on the role of software platforms, and around these platforms so-called ecosystems evolve. Evans et al. (2006) describe a software platform as “a software program that makes services available to other software programs through Application Programming Interfaces (APIs)”.2 Jansen et al. (2009) define such an ecosystem around a platform as “a set of actors functioning as a unit and interacting with a shared market for software and services, together with the relationships among them. These relationships are frequently underpinned by a common technological platform or market and operate through the exchange of information, resources, and artifacts.” The idea of offering software systems, which are based on platforms, in combination with complementary products from an “ecosystem” is applied throughout the software industry. This is not a new phenomenon: Around the first operating systems, “ecosystems” of applications had already evolved. Current examples for developing ecosystems are both Apple, with the AppStore, and Google, with the Android Marketplace. A similar constellation can be found in the area of service-oriented architectures (SOA): SOA services from different vendors can be integrated on the basis of SOA platforms. Moreover, the evolvement of ecosystems is observable in the Software-as-a-Service (SaaS) market (Cusumano 2010a; Cusumano 2010b).

Enterprises increasingly adopt value chain improving technologies to retain a competitive position in a rapidly changing, uncertain, and demanding environment. Due to its hyper-competitive market, especially the financial services industry is exposed to a high level of environmental turbulence and resulting uncertainty (Ang and Cummings 1997). The ongoing need to realize and adapt to these environmental changes is reflected by the concept of agility which describes one of the key success factors for organizations striving to stay competitive, even in uncertain and turbulent markets (Dove 2001).

For a long time research on the management of IS outsourcing projects viewed relational and contractual governance as substitutes. However, subsequent studies provided empirical evidence for the complementary view. Recently, some authors supported the notion that relational and contractual governance mechanisms can simultaneously be complements and substitutes. Given these inconsistencies the question arises how contractual and relational governance become substitutes or complements. We investigate whether the relationship between governance mechanisms is the outcome of distinctprocesses of interaction between contractual and relational governance. For that purpose, we conduct an exploratory multiple-case study of five IS outsourcing projects at a leading global bank. We identify three archetypical processes illustrating how the interaction between relational and contractual governance can result in a complementary relationship. In addition, we discover one process explaining their substitution. The results of our study propose a shift in perspective. While former studies focused on explaining whether contractual and relational governance are complements or substitutes, we answer the question how and why they become complements and substitutes. Based on our findings, we give implications for further research.

Due to new information and communication technologies, organizations can simplify the work of their employees, which is the largely overlooked perspective in IS research (Choudrie and Dwivedi 2006). In addition, households could integrate these technological innovations within their daily routine to handle ordinary or uncommon tasks within short periods of time. One essential innovation of the last years was the introduction of Social Network Sites (SNS), which can be defined as “online shared interactive spaces, in which a group of people use a repertoire of technological features (forums, newsgroups, messaging) to carry out a wide range of social interaction” (Khan and Jarvenpaa 2010; Jones et al 2004).

The information systems (IS) research community is characterized by a large diversity of research approaches and topics. Although empirical quantitative research approaches dominate (Orlikowski et al. 1991), new research strategies are on the rise. Two research strategies that have received increasing scholarly attention recently are design science research (DSR) and the grounded theory method (GTM). For example, the European Journal of Information Systems (EJIS) recently published a special issue on DSR edited by Baskerville (2008). In addition, there is a call for papers by the same journal for a special issue on the GTM which will appear in the near future.

Computer support for collaborative modeling (or group modeling) has been an issue of research for two decades now. Early studies include Dean et al. (1994) and they found that a collaborative tool (basically a text editor) for the IDEF0 activity modeling language was able to reduce modeling time substantially by splitting large groups of more than 20 people into smaller teams each of which would work on a computer to elaborate a different chunk of a large model.

The importance of online shopping has grown remarkably over the last decade. In 2009, every West European spent on average € 483 online and this amount is expected to grow to € 601 in 2014. In Germany, the number of online shoppers has almost doubled since 2000: 44% of all adults regularly buy products onlinetoday. In Western Europe, online sales reached € 68 billion in 2009 and Forrester research forecasts it will reach € 114 billion by 2014 with an 11% compound annual growth rate.

More than 10% of the German gross domestic product is spent on health related services every year summing up to 263bn € in 2008 (Destatis 2010). A large proportion of these funds is invested into information technology (IT). Although solid empirical data on the allocation of these funds is scarce, the available studies offer interesting insights into the importance of IT in German health care: IT accounts for an estimated 2.9-3.7% of hospitals overall budget (VHitG 2010) and for an estimated ~14% of hospital investments (Blum and Schilz 2005).

Social relationships within multinational teams are often burdened by cultural differences between the team members. Severe difficulties arising from such differences include conflict, mistrust, and miscommunication (Salk and Brannen,2000). This in turn hampers the creation of social capital within the team and thus leads to sub-optimal knowledge exchange, collaboration, and project performance. Consequently, numerous studies consider cultural differences in the context of multinational teams and propose various management actions that can be taken to overcome resulting problems in the network of relationships among team members (e.g., Carmel, 1999; Carmel and Agarwal, 2001; Earley and Mosakowski, 2000; Govindarajan and Gupta, 2001; Oshri et al., 2007; Sarker and Sarker, 2009; Walsham, 2002).

Competition in the logistics sector significantly increases driven by high cost pressure and new legal regulations. In particular, the new rules for CO2 emissions increase the pressure on logistics companies to improve their network efficiency. On the strategic level, the network efficiency of small package shippers (SPS) mainly depends on the locations of hubs and depots. Since customer demand as well as customer locations vary within the planning horizon of a strategic decision, which is about 10-15 years, a reasonable approximation of those values and a powerful planning tool are required.

The amount of information produced by and available to every member of today’s society grows at a stunning pace. Driven by the importance of an efficient information distribution, a large field of heterogeneous research streams has developed in the course of the last four decades in various scientific domains. Major and important contributions have been created with respect to the behavior of organizations, groups and individuals towards the acquisition and processing of information. Furthermore, the outcome effects of these activities such as decision-making and sense-making have been investigated. This article focuses on literature dealing with the exploration and explanation of specific behavioral patterns occurring when individuals interact with information in computer-mediated contexts.