Month: May 2021

On the video below, I apply the distinction between gardeners and architects to academic writing.

If you want to listen to a great discussion of the original concept in fiction and literature, the video below by Brandon Sanderson is worth the watch.

In the video below I show how I moved from a rough outline to a clean outline for the theory section of a paper. Enjoy!

Final outline (paragraphs with asterisks are quotes from papers)

0. The current model of IS success and some of its applications offer some openings to improve the specification of agency therein, and highlight the challenges that need to be addressed when doing so. 0.*. Contrasting this model with the broader specification of the role of agency in IS provides a template / path to improve the role of agency in the model of IS success and outlines some of the benefits that justify doing so. 

1. The opportunity to improve the specification of agency in the model of IS success

1.1. Research on IS success has always specified a role for users. 

(NOTE: Here I am specifying the first type of use: actualization)

1.1.*. This is evident in the the DeL/McL model which remains one of the key frameworks to explain IS success.

1.1.*.*. <The role of users in the extended DeL/McL model>

1.1.1. This role has expanded as models of IS success have been revised and extended.

1.1.1.*. This is aptly illustrated in the development and application of the DeL/McL model 

1.1.1.*.*. <The role of users in the application of the DeL/McL model to BI>

1.1.2 Overall, this shows progress in specifying the role of agency in IS success / shows that there are more avenues to incorporare agency in the model of IS success.

1.1.2.*. But there is still a big gap between how agency is specified in IS success and the efforts to improve how agency is specified in the research on IS writ large. 

1.2. Research on the use of ISs in organizations and their effects has a deeper and broader specification of the role of users.

(NOTE: Here I am specifying the second type of use: improvisation / adaptation).

1.2.1. This specification is deeper because it takes the effects of IT and even IT iself as an accomplishment of practice.

1.2.2. This specification is broader because it shows that employees also improvise and adapt information systems to their situated conditions for action.

1.3. The potential of agency in the model of IS success

1.3.1.  The model of IS success has acknowledged improvisation, but has dismissed it as an obstacle to information system success.  

1.3.2. However, research on agency in MIS have improved the specification of key individual components of IS success in ways that have not only advanced theory, but which have also offered practical advice for managers.

1.3.2.*. <List elements of model that have benefitted from MIS/agency> 

1.3.3. These studies suggest that introducing agency in the model of IS success can improve the specification of a broader set of components of IS success, broadening theoretical implications and improving practical implications / advice.

1.3.*. In the study reported next, we specify and extend the role of agency in IS success by explaining the role of analysts in <improving the quality of managers decisions>

1.4. Specifying the role of agency in IS success by exploring agency in MSSs (BISs). 

1.4.1. Exploring the role of agency in MSSs allows us to address a key obstacle to <a good specification of agency in IS success>: the limited specification of agency in MSSs compared with the rich specification of agency in MISs.

1.4.1.*. This is an obstacle because MSSs are at the end of of the upward flow of information and therefore mediate the effect of MISs (and other ISs) on the quality of decision making / success of MISs. 

1.4.2. Literature reviews show that MSSs suffer from the same limited take of agency adopted by research on IS success

1.4.3. 

1.4.3.1. However, some studies that look at the role of agency on MIS have provided some empirical evidence of a similar role of agency in MSSs. 

1.4.3.2. Moreover, research on MSSs has argued for the distributed nature of analysis

*.

We have one final point to make before leaving this discussion of the process model in Figure 2. This is that value from BA may be generated by many people in an organization, not just data scientists (Davenport & Patil, 2012). For this reason, the words ‘executed over and over again in different parts of the organization’ in Figure 2 are very important. Our argument is that (a) many, many people throughout an organization may have access to BA tools, (b) all of them may have useful insights, and (c) one million ‘ten-dollar’ insights are worth as much as one ‘ten-million dollar’ insight. In other words, repeated execution of the process in panel A of Figure 2, by people all over the organization, is the fundamental driver of benefits from business analytics.

*. Analysis is a distributed, rather than individual process: “A key emphasis in many of these studies is that individual managers, as skilled rhetoricians, are – through their strategic framing tactics – able to shape and direct the interpretations of organizational members and other stakeholders towards a new set of interpretive frames (e.g., Fiss & Zajac, XXXX)[…]there is very little similar research within the management and organizational literature that explores detailed social interactions of this kind, and how – and under what conditions – it leads to the establishment of joint interactive frames. […]

1.4.3.3. Moreover research on framing / decision making also highlights the fundamentally practical nature of analysis

*. Another area for further research that we wish to highlight involves the experiential grounding of frames in actual practices. This interconnection is important not only to better understanding the initiation, diffusion, and institutionalization of institutional change (Smets, Morris, & Greenwood, 2012), but also to offsetting an otherwise more narrow view of framing as a largely symbolic and cognitive process of meaning-making that stands apart from the practices and immediate experiences of individuals and groups.

*.*. 

“Although technology can act as a rationality carrier, it is insufficient for developing organizational capabilities by itself (Ulrich & Lake, 1991). Hence, organizational researchers have called for research on rationality persistence in organizations via its distribution between humans and technology artifacts (Latour, 2005). Fostering analytical decision making values in employees is one way to ensure rationality persistence (Sadler-Smith & Shefy, 2004). Decision makers need to undergo a systematic shift in their values to accept and embrace analytical decision making as a belief system. Our analytical decision making orientation construct represents the encouragement that employees at all levels of the organization perceive to make decisions based on information and evidence and to support ideas, opinions, proposals, and so on with facts and figures wherever possible. Advanced organizations in this direction show widespread respect for measurement and evaluation. In the context of BI, such organizations readily use and exploit technologies that infuse rationality in decision making; they routinely perform complex analyses on large data sets to solve difficult problems, and their routine business processes incorporate analytical processing.”

*.

Ergo, more recent studies (Fink et al., 2017; Shollo & Galliers, 2016) have criticized overemphasizing technology without accounting for the human ‘sense-making’ processes. As Sharma, Mithas, and Kankanhalli, 2014, p. 435) “insights emerge out of an active process of engagement between analysts and business managers using the data and analytic tools to uncover new knowledge.” Accordingly, Shollo and Galliers (2016) have provided empirical evidence of the BI&A agency in data selection and problem articulation for the active process of knowing.

*.

Ergo, more recent studies (Fink et al., 2017; Shollo & Galliers, 2016) have criticized overemphasizing technology without accounting for the human ‘sense-making’ processes. As Sharma, Mithas, and Kankanhalli, 2014, p. 435) “insights emerge out of an active process of engagement between analysts and business managers using the data and analytic tools to uncover new knowledge.” Accordingly, Shollo and Galliers (2016) have provided empirical evidence of the BI&A agency in data selection and problem articulation for the active process of knowing.

1.4.4.The insights provided by research on agency in MIS show that a similar effort in research on MSS can not only provide improved specifications of the process of computer-assisted analysis in organizations, but also introduce an alternative / complementary path for IS success because it offers the opportunity complete and to link the effects of agency on the model of IS success. 

1.4.4.1. Research on MIS has shown that the solutions to MSS problems, and improving its conditions for success can be solved by human / organizational solutions rather than just by technological solutions (cf. Paper on EKPs).

*. 

analytic leadership is ‘the extent to which people in any organi- zational unit take leadership of initiatives or projects to increase use of business analytics for organizational gain’. With respect to leadership, Davenport et al. (2010, p.57) say: ‘If we had to choose a single factor to determine how analytical an organization will be, it would be lead- ership. … Leaders have a strong influence on culture and can mobilize people, money, and time to help push for more analytical decision making’

1.4.4.2. In Ain 2019, BI chanllenges reduce BI effectiveness. In my paper, BI challenges lead to new practices to overcome such challenges and ensure effectiveness.

1.4.4.*. Introducing agency in the model of MSS success can also help to address several shortcomings / bottleneckes / open questions of research on this type of information technology, cf. opening of very salty MISQ paper

1.4.4. In the study reported next, we explore the role of agency in an MSS and use it to specify the role of agency in IS success. 

Rough draft outline

1. The model of IS success has yet to benefit from the extensive theoretical development of the role of agency in research on MIS. 

1.1. The core model of IS success does recognize the role of agency by including ‘use’ as one of its components

1.2. Applications of this core model have further specified the link between IS use and IS success 

1.3. This has provided a detailed explanation of the role of users / use in IS success, and emphasized the importance of taking agency into account when specifying a model if IS success. 

1.4. However, comparing how models of IS success specify agency with how agency has been incorporated in the research on IS writ large, it is clear that there is ample space to improve the specification of the role of agency in the model of IS success.

2. It is necessary to improve the specification of the role of agency in the model of IS success because, the specification of people as ‘users’ limits the explanatory potential of these models for technologies such as MISs and MSSs who collect, provide and analyze the information that organizations use to make decisions.

3. Next we specify the current specification of agency in research on IS success and highlight the theoretical potential of improving the specificaiton of agency therein. This is followed by the specification of the methodological procedures that we followed to build a model of IS success that improves the specification of the role of agency therein.

(/EXTENDED SECTION OUTLINE)

(DETAILED PAPER OUTLINE)

0. The model of IS success has been slow to incorporate agency.

0.*. This limits the explanatory potential of these models for technologies such as MISs and MSSs who collect, provide and analyze the information that organizations use to make decisions.

1. The opportunity for agency in the model of IS success

1.1. Part of the reason is that groundwork for the model of IS success has been established in the very early stages of the theorization of the role of agency in information systems.

1.1.1. The DeLorean model, which recent literature reviews have shown to still be the central framework for research on IS success was established in 1992

1.1.2. This is contemporary with early applications of structuration theory.

1.1.3. There have been developments, extensions and applications of this model but these have not included agency.

1.1.4. However, some like the application of this model to the upward flow of information and analysis have opened up several avenues to incorporare agency in the model of IS success

1.2. Lack of agency in the model of IS success is also an effect of the gap between the specification of the role of agency in MIS and MSS

1.2.1. IS succcess in the upward flow of representation is very much focused on the decision making processes, where MSSs play a key role: as a key role of MISs is to provide information for MSSs, it is incorrect to establish the succses of MISs on their own. 

1.2.2. MSSs have benefitted from far less research on agency than MISs and even from research on IT as a whole. 

1.2.2.1. There has been a growing number of papers that have uncovered the role of agency in how MISs collect and report information up the organization.

1.2.2.2. The literature on MSS has yet to benefit from an effort to specify the role of agency in the process of computer-assisted analysis

1.2.2.3. There has been some research on the role of use and users, but most of this research leaves out the appropriations and improvisations documented by research on MIS.

*.

We have one final point to make before leaving this discussion of the process model in Figure 2. This is that value from BA may be generated by many people in an organization, not just data scientists (Davenport & Patil, 2012). For this reason, the words ‘executed over and over again in different parts of the organization’ in Figure 2 are very important. Our argument is that (a) many, many people throughout an organization may have access to BA tools, (b) all of them may have useful insights, and (c) one million ‘ten-dollar’ insights are worth as much as one ‘ten-million dollar’ insight. In other words, repeated execution of the process in panel A of Figure 2, by people all over the organization, is the fundamental driver of benefits from business analytics.

*. 

analytic leadership is ‘the extent to which people in any organi- zational unit take leadership of initiatives or projects to increase use of business analytics for organizational gain’. With respect to leadership, Davenport et al. (2010, p.57) say: ‘If we had to choose a single factor to determine how analytical an organization will be, it would be lead- ership. … Leaders have a strong influence on culture and can mobilize people, money, and time to help push for more analytical decision making’

*. 

Analytical people: The extent to which there are people within the organizational unit with an analytic mindset who help drive business value from BA. (Davenport et al., 2010) 

*.*. In this model analytical people are consumers, rather than producers of data and analyses (they do produce analyses, but for themselves, not to shape the decisions of others).

1.2.2.*. Instead, the few papers that document use thus, emphasize the negative effects improvisations and appropriations.

1.2.2.*. “The problem to date has been a too simplistic definition of this complex variable. Simply saying that more use will yield more benefits, without considering the nature of this use, is clearly insufficient. Researchers must also consider the nature, extent, quality, and appropriateness of the system use. The nature of system use could be addressed by determining whether the full functionality of a system is being used for the intended purposes.”

2. The potential of agency in the model of IS success

2.0. Research on agency MIS is more than a model of the potential of agency to advance research on MSS.

2.1. Research on agency in MIS have improved the specification of key individual components of IS success in ways that have not only advanced theory, but which have also offered practical advice for managers.

2.1.*. <List elements of model that have benefitted from MIS/agency> (maybe do a table that includes #2.1 and #2.2)

2.1.*.*. Notes:

*. Cf. Laumer: Amount of use explains success, we add that type of use also explains success.

2.2. These studies suggest that introducing agency in MSS can improve the specification of a broader set of components of IS success, broadening theoretical implications and improving practical implications / advice.

2.2.*. <List elements of model that can benefit from new MSS/agency> (maybe do a table that includes #2.1 and #2.2) 

2.2.*.*. Notes:

*.There is also a disconnect between the collective nature of IT use in MIS and the individual nature of IT use in MSS

*. Value of IS is different to different people, which basically means that effectiveness requires adaptation, which is what I find in my research. (Mirani 1998) 

*. Applications of the model of IT success (incl applications to BIS cf. Clark 2007) show that the model of IT success can only start with properties of IT if we assume that those properties are stable / IT features and not an accomplishment of people

* Applications of the model of IT success (incl applications to BIS cf. Clark 2007, *AND* Wixom 2001) show that the model of IT success needs an additional set of variables to avoid IT centric explanations of success

*. Analysis is a distributed, rather than individual process: “A key emphasis in many of these studies is that individual managers, as skilled rhetoricians, are – through their strategic framing tactics – able to shape and direct the interpretations of organizational members and other stakeholders towards a new set of interpretive frames (e.g., Fiss & Zajac, XXXX)[…]there is very little similar research within the management and organizational literature that explores detailed social interactions of this kind, and how – and under what conditions – it leads to the establishment of joint interactive frames. […]

*. Another area for further research that we wish to highlight involves the experiential grounding of frames in actual practices. This interconnection is important not only to better understanding the initiation, diffusion, and institutionalization of institutional change (Smets, Morris, & Greenwood, 2012), but also to offsetting an otherwise more narrow view of framing as a largely symbolic and cognitive process of meaning-making that stands apart from the practices and immediate experiences of individuals and groups. 

*. Analytical people: The extent to which there are people within the organizational unit with an analytic mindset who help drive business value from BA. (Davenport et al., 2010) 

*.*. In this model analytical people are consumers, rather than producers of data and analyses (they do produce analyses, but for themselves, not to shape the decisions of others).

*.*. “Although technology can act as a rationality carrier, it is insufficient for developing organizational capabilities by itself (Ulrich & Lake, 1991). Hence, organizational researchers have called for research on rationality persistence in organizations via its distribution between humans and technology artifacts (Latour, 2005). Fostering analytical decision making values in employees is one way to ensure rationality persistence (Sadler-Smith & Shefy, 2004). Decision makers need to undergo a systematic shift in their values to accept and embrace analytical decision making as a belief system. Our analytical decision making orientation construct represents the encouragement that employees at all levels of the organization perceive to make decisions based on information and evidence and to support ideas, opinions, proposals, and so on with facts and figures wherever possible. Advanced organizations in this direction show widespread respect for measurement and evaluation. In the context of BI, such organizations readily use and exploit technologies that infuse rationality in decision making; they routinely perform complex analyses on large data sets to solve difficult problems, and their routine business processes incorporate analytical processing.”

*.

Ergo, more recent studies (Fink et al., 2017; Shollo & Galliers, 2016) have criticized overemphasizing technology without accounting for the human ‘sense-making’ processes. As Sharma, Mithas, and Kankanhalli, 2014, p. 435) “insights emerge out of an active process of engagement between analysts and business managers using the data and analytic tools to uncover new knowledge.” Accordingly, Shollo and Galliers (2016) have provided empirical evidence of the BI&A agency in data selection and problem articulation for the active process of knowing.

2.3. the insights provided by research on agency in MIS show that a similar effort in research on MSS can not only provide improved specifications of the process of computer-assisted analysis in organizations, but also introduce an alternative / complementary path for IS success because it offers the opportunity complete and to link the effects of agency on the model of IS success. 

2.3.*.

*. Research on MIS has shown that the solutions to MSS problems, and improving its conditions for success can be solved by human / organizational solutions rather than just by technological solutions (cf. Paper on EKPs).

*. In Ain 2019, BI chanllenges reduce BI effectiveness. In my paper, BI challenges lead to new practices to overcome such challenges and ensure effectiveness.

*. *. Kaplan (2008) argues that a key limitation of prior research on strategic frames is its persistent focus on cognitive aspects and their consequences (Nadkarni & Narayanan, 2007; Gilbert, 2006). As a result, research often backgrounds the actual processes by which frames are socially constructed and negotiated. 

*. ”Building on Petter et al’s (2012) identification of the importance of information quality, we argue that if users perceive the format or the presentation of information as a threat, this will lower the benefits of the information for their organizations and organizations should redesign the format of the information. Similarly, if users perceive the usability of the information as a threat to their task, organizations should better align the usability of the information with users’ tasks. In other words, the inter- ventions an organization would implement to improve information quality differ along these two dimensions.”

*.

*. DeLone and McLean (2003) in their ten-year update of the DeLone and Mclean success model (1992) depict ‘‘net benefits’’ as the most important success measure for IS, with net benefits referring to ‘‘cost savings, expanded markets, incremental additional sales, reduced search costs and time savings’’ (p. 26). Their updated model is a dynamic one, with the realized net benefits feeding back to further intention to use and user satis- faction. The notion of organizational change and transformation as an important aspect of success, however, is not included. Further, an integrative framework for information technology business value published recently by Melville et al. (2004) is uni-directional and omits the cyclical processes of organizational transformation and learning and the time-lagged nature of benefits that have been shown in econometric studies to be vital in understanding IT value generation. Although these authors recognize complementary organizational changes as a factor in achieving value from IT, they do not consider chan- ged organizational forms and capabilities themselves as assets that result from IT imple- mentation. (IMPTT: In the discussion, I can talk about IS success as having an additional dimension which is IS/Organizational transformation as a new net benefit cf. GREGOR ET AL 2006) / Notice that this comes from research on IT value, thread carefully. 

*. *

Although the general IT literature is fairly consistent in classifying IT assets as either physical or human [17,64,79], it includes different ways in which the two types of assets are related to each other. One approach is that IT-related knowledge and skills are complementary to physical IT assets, implying that they are orthogonal to each other [6]. An alternative approach is that the experience and expertise of IT personnel may constrain the quality of physical IT assets [30], and therefore a model that accounts for the effect of human IT assets on physical ones is superior to alternative models of reversed causality or orthogonality [36].

2.4. Introducing agency in the model of MSS success can also help to address several shortcomings / bottleneckes / open questions of research on this type of information technology, cf. opening of very salty MISQ paper

3. My paper motivates, illustrates and specifies this project by addressing the following research question: <research question>.

3.*. (Note that BI is a good setting to add agency to the model of IS success because BI has detailed model of IS success and this model has several variables that link to use)