Self-Expansion or Internalization as the Two Processes of Vertical Integration: What Informs the Decision?

In vertical integration literature, the two processes leading to vertical integration, namely, (1) self-expansion of the scope of activities based on internal capabilities and (2) internalization of activities with external capabilities have not been distinguished. However, using internal capabilities or incorporating external capabilities is an alternative decision for managers and distinguishing them is crucial in practice. The purpose of this study is to distinguish self-expansion separated from internalization and to explain systematically when they likely occur. This study develops a unique vertical integration model by integrating transaction cost economics and the capability approach. With the model, we systematically analyzed the occurrence of (1) self-expansion and (2) internalization. Results reveal that the firm prefers self-expansion to internalization if it is easy to build the capabilities internally or difficult to procure them from outside the firm and if the costs of acquiring a firm or business with the required capabilities or the governance costs of the activities with external capabilities are high and vice versa. Our model leads to more understanding of vertical integration.

The presence of irrelevant alternatives paradoxically increases confidence in perceptual decisions

Confidence in perceptual decisions often reflects the probability of being correct. Hence, we predicted that confidence should be unaffected or be minimally decreased by the presence of irrelevant alternatives. To test this prediction, we designed three experiments. In Experiment 1, participants had to identify the largest geometrical shape among two or three alternatives. In the three-alternative condition, one of the shapes was much smaller than the other two, being a clearly incorrect choice. Counter-intuitively, all else being equal, confidence was higher when the irrelevant alternative was present. We accounted for this effect with a computational model where confidence increases monotonically with the number of irrelevant alternatives, a prediction we confirmed in Experiment 2. In Experiment 3, we evaluated whether this effect replicated in a categorical task, but we did not find supporting evidence. Our findings stimulate the use of multi-alternative decision-making tasks to build a thorough understanding of confidence.

The Aggregation–Learning Trade-off

Organizational decision making that leverages the collective wisdom and knowledge of multiple individuals is ubiquitous in management practice, occurring in settings such as top management teams, corporate boards, and the teams and groups that pervade modern organizations. Decision-making structures employed by organizations shape the effectiveness of knowledge aggregation. We argue that decision-making structures play a second crucial role in that they shape the learning of individuals that participate in organizational decision making. In organizational decision making, individuals do not engage in learning by doing but, rather, in what we call learning by participating, which is distinct in that individuals learn by receiving feedback not on their own choices but, rather, on the choice made by the organization. We examine how learning by participating influences the efficacy of aggregation and learning across alternative decision-making structures and group sizes. Our central insight is that learning by participating leads to an aggregation–learning trade-off in which structures that are effective in aggregating information can be ineffective in fostering individual learning. We discuss implications for research on organizations in the areas of learning, microfoundations, teams, and crowds.

Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making

There has been debate about whether addition of an irrelevant distractor option to an otherwise binary decision influences which of the two choices is taken. We show that disparate views on this question are reconciled if distractors exert two opposing but not mutually exclusive effects. Each effect predominates in a different part of decision space: 1) a positive distractor effect predicts high-value distractors improve decision-making; 2) a negative distractor effect, of the type associated with divisive normalisation models, entails decreased accuracy with increased distractor values. Here, we demonstrate both distractor effects coexist in human decision making but in different parts of a decision space defined by the choice values. We show disruption of the medial intraparietal area (MIP) by transcranial magnetic stimulation (TMS) increases positive distractor effects at the expense of negative distractor effects. Furthermore, individuals with larger MIP volumes are also less susceptible to the disruption induced by TMS. These findings also demonstrate a causal link between MIP and the impact of distractors on decision-making via divisive normalization.

Humans balance breadth and depth: Near-optimal performance in many-alternative decision making

Many everyday life decisions require allocating finite resources, such as attention or time, to examine multiple available options, like choosing an online food supplier. In these cases, our search resources can be spread across many options (breadth) or focused on a few of them (depth). Whilst theoretical work has described how finite resources should be allocated to maximise utility in these problems, evidence about how humans balance breadth and depth is lacking. We introduce a novel experimental paradigm where humans make a many-alternative decision under finite resources. In an imaginary scenario, participants allocate a finite budget to sample amongst multiple apricot suppliers in order to estimate the quality of their fruits, and ultimately choose the best one. We found that at low budget capacity participants sample as many suppliers as possible, and thus prefer breadth, whereas at high capacities participants sample just a few chosen alternatives in depth, and intentionally ignore the rest. The number of alternatives sampled increases with capacity following a power law with an exponent close to 0.75. In richer environments, where good outcomes are more likely, humans further favour depth. Participants deviate from optimality and tend to allocate capacity amongst the selected alternatives more homogeneously than it would be optimal, but the impact on the outcome is small. Overall, our results undercover a rich phenomenology of close-to-optimal behaviour and biases in complex choices.

4. EU Law: Sources, Forms, and Law-Making

This chapter takes an overall view of the EU legal order and examines its legal system, including the elements which are either different from or similar to member states’ legal systems. It begins by taking an overall view of the EU legal order, the different forms of EU law, and the various sources of law contributing to this legal order, in particular now the rich source of human and fundamental rights in the EU legal order. It considers the non-strictly legally binding rules known as ‘soft law’. It also looks at the ways or processes by which the binding laws are made and reviews alternative decision-making and law-making developments.

Design of the Vertical Roundness Tester Machine Using the AHP Method (Analytical Hierarchy Process) Through the DFM Approach (Design for Manufacturing)

The Roundness Tester Machine is a tool used to take measurements that are shown to check the Roundness of an object or to find out whether an object is really round or not when viewed carefully using a measuring instrument. DFM (Design for Manufacturing) is a method for reducing production costs by estimating production costs through reducing component costs, assembly costs, and other production supporting costs based on design submission data without reducing product quality. AHP (Analytical Hierarchy Process) method was chosen as a method to determine the optimal Vertical Roundness Tester Machine design based on a questionnaire given to the expert, to choose the best alternative decision. The questionnaire was created to get priority customer needs which was then used for the initial design. The next stage is selecting the optimal design using AHP which involves experts based on indicators of a product. The highest indicator value obtained on the Vertical Roundness Tester Machine is the accuracy indicator with a value of 48.52%. Then in choosing the optimal design in the DFM analysis, namely in alternative 3, where alternative 3 is the design with the lowest cost so as to minimize the cost of making a Vertical Roundness Tester Machine. The manufacturing cost for alternative design 3 is Rp. 4,173,000.

Deciding how to decide on public goods provision: The role of instrumental versus intrinsic motives

What determines citizens’ preferences over alternative decision-making procedures – the personal gain associated with a procedure, or the intrinsic value assigned to it? To answer this question, we present results of a laboratory experiment in which participants select a procedure to decide on the provision of a public good. In the first stage, they choose between majority voting and delegation to a welfare-maximizing algorithm. In the second stage, subjects either vote on the public good provision, or the decision is taken by the algorithm. We define three experimental conditions in which participants receive information about whether a majority in the group faces a positive or negative pay-off from the public good provision, about whether there is a positive group benefit from its provision, or neither kind of information. Findings confirm the importance of instrumental motives in procedural choices. At the same time, however, a significant share of participants chose a procedure that does not maximize their individual benefit. While majority voting seems to be preferred for intrinsic values of fairness and equality, support for delegation to the welfare-maximizing algorithm increases if the group benefit from a public good is known – even in participants who are net payers for its provision.

Automatic Task Machine (ATM) Design for Logistic Package by Method Analytical Hierarchy Process (AHP) Through Approach the Design for Manufacturing (DFM)

The Automatic Task Machine (ATM) machine for logistics packages is a machine vision to measure the dimensions and other components in form load cell, which serves to measure the mass of an object. This machine design was development the addition of components such as insert card, screens, navigation buttons, receipt printers, automatic package doors and a storage room delivery mechanism. Method of Analytical Hierarchy Process (AHP) was chosen to determine the ATM design for the optimal logistics package for the best alternative decision. The questionnaires were made to get priority consumer needs, which it used for the initial design. The consumer needs questionnaire was based on several indicators, namely: ergonomics, measurement of dimensions and weight, package transmission and package storage. The next stage was selecting the optimal design using AHP, which involves Expert based on the indicator of a product. The highest indicator value obtained for the logistics package ATM is "dimension and weight" with a value of 5.22 and the optimal design choice was "alternative 3". The optimal design choice was analyzed using the Design for Manufacturing (DFM) approach to consider the cost of manufacturing product, which aims to minimize the cost of making ATMs for logistics packages.

Excitatory-inhibitory tone shapes decision strategies in a hierarchical neural network model of multi-attribute choice

We are constantly faced with decisions between alternatives defined by multiple attributes, necessitating an evaluation and integration of different information sources. Time-varying signals in multiple brain areas are implicated in decision-making; but we lack a rigorous biophysical description of how basic circuit properties, such as excitatory-inhibitory (E/I) tone and cascading nonlinearities, shape attribute processing and choice behavior. Furthermore, how such properties govern choice performance under varying levels of environmental uncertainty is unknown. We investigated two-attribute, two-alternative decision-making in a dynamical, cascading nonlinear neural network with three layers: an input layer encoding choice alternative attribute values; an intermediate layer of modules processing separate attributes; and a final layer producing the decision. Depending on intermediate layer E/I tone, the network displays distinct regimes characterized by linear (I), convex (II) or concave (III) choice indifference curves. In regimes I and II, each option’s attribute information is additively integrated. In regime III, time-varying nonlinear operations amplify the separation between offer distributions by selectively attending to the attribute with the larger differences in input values. At low environmental uncertainty, a linear combination most consistently selects higher valued alternatives. However, at high environmental uncertainty, regime III is more likely than a linear operation to select alternatives with higher value. Furthermore, there are conditions where readout from the intermediate layer could be experimentally indistinguishable from the final layer. Finally, these principles are used to examine multi-attribute decisions in systems with reduced inhibitory tone, leading to predictions of different choice patterns and overall performance between those with restrictions on inhibitory tone and neurotypicals.