To give one more example: the Times of India(31 December 2004) reported that Sunil Dutt, then Union minister for sports and youth affairs, could not identify the taxi driver accused of rash driving in a case dating back twenty years. Apparently, on 12 July 1984 Sunil Dutt and his companions were driving down 17th Road, Khar, when a taxi driver overtook their car rashly and even threatened to kill Dutt for warning him. After twenty years, when Dutt was asked to identify the driver, he refused as his conscience did not let him do what he was not sure about.
Surely we are a grand democracy of defections. Our guilty are free to defect against the spirit of the judiciary through innumerable adjournments; our municipalities are free to defect by letting our towns become seething ghettos; our politicians are free to defect taking democracy for a ride; our civil servants are free to defect just serving time; our universities are free to defect not carrying out any research or quality teaching; our judicial system is free to defect not dispensing timely justice; and we as a people are free to defect driving on the right-hand side of the road and spitting into each other’s eyes. When the returning defections complete the D–D loop, we have a reverberating and throbbing India, a functioning anarchy, as Bertrand Russell called us.
Let us move on to the flip side of self-regulation, namely, free riding.
CHAPTER 7
Are We the World’s Biggest Free Riders?
There is a parable about an ancient Indian king. He couldn’t sleep worrying about the integrity of his subjects. So he decided to test them out, once and for all, to cure himself of insomnia. He proclaimed to all his subjects that he wanted each one of them to pour a glass of milk into a large cauldron kept at the town centre that night. The cover of darkness was to allay fears that the contents would be monitored as people poured the glass of milk into the receptacle. The next morning the king went to inspect the contents, only to find the vessel full of crystal clear water. Clearly, each of the subjects thought his or her glass of water would go unnoticed in a cauldron full of milk contributed by the others.
FREE RIDING AT A GALLOP
What our ancient king witnessed was the problem of free riding in action, or what Garrett Hardin called the Tragedy of the Commons.1
Free riding or Tragedy of the Commons is a problem not unique to us, Indians. Wherever there is public good, there are bound to be free riders. What do we mean by public good? Thaler offers a good definition.2 According to him, a public good has the following two properties:
Once it is provided to one, it is costless to provide it to everyone else.
It is difficult to prevent one who doesn’t pay for the good from using it.
Typical examples of ‘public good’ are the public radio and television, internet, non-toll highways, bridges, parks, temples, canals, sidewalks and village commons. When there is public good, there are bound to be those who will free ride. Free riders, even if they enjoy the benefits of the public good, will not pay for it because there is no ‘rational’ reason why they should.
Yet, not everybody free rides. Many of us do pay our taxes even if we could probably get away without having to; many of us do contribute to charities; and probably in real life that king would have found a feeble white solution in the cauldron, since there are always some who pay up for a variety of motives.
FREE-RIDING EXPERIMENTS
Behavioural researchers such as Thaler, Oliver and Mark,3 among others, have done much work trying to find out why people do or do not free ride. The works include some delightful experiments, many of which I have enjoyed replicating for MBA students in India and abroad.
You too can replicate some of Thaler’s experiments at your next party. Let’s say you have ten guests. Give Rs 100 (real or notional) to each one of them. Tell them that they may either keep the money for themselves or contribute it to a common corpus. Tell them that the money contributed into the common kitty will be multiplied by a certain factor that is greater than one, but less than the number of participants, say, two. This multiplication simulates the fact that when contribution is made to public good, the government typically adds to that kitty, enhancing the kitty available for the greater good of all. You then tell them that for each participant contributing his Rs 100 to the corpus, you will double the amount and distribute it equally among all the ten participants, irrespective of whether or not they contributed to the kitty. The information on who contributed and who did not may be kept a secret, replicating the fact that in real life free riders are not always exposed.
Obviously, if all the ten participants contribute Rs 100 to the kitty, everybody takes home Rs 200, as the contribution to the kitty is doubled and equally divided among all. The participants, as a whole, double their wealth from an initial principal of Rs 1000 to Rs 2000. On the other hand, suppose everybody except one of your guests contributed Rs 100 to the kitty, then all the nine contributors (or cooperators) go home with Rs 180 each, while the free rider or the defector takes home Rs 280. The total capital of the ten participants, as a whole, increases from Rs 1000 to Rs 1900, that is, Rs 100 short of the maximum possible. Similarly, if half of them contribute while the other half do not, the five contributors take home only Rs 100 while the five free riders pocket 200 each. The total capital of the ten participants in this case goes up from Rs 1000 to Rs 1500 only. In short, it is obvious that if one contributes nothing, while the others do, one is better off than the others. But the strategy of free riding ensures that the group, as a whole, does not prosper. Yet, to human nature in general and us Indians in particular, it appears very rational to free ride.
It’s fun to watch the game unfold. You can also give the game many twists and turns like allowing participants to make partial or full contribution, keeping the responses opaque or transparent; playing the game just once or playing it over and over again, and having the contributions made in single stage or multiple stages.
SOME VARIATIONS
Here is one interesting variation. If a minimum of six of the ten participants contribute Rs 100 each to the common kitty, each of the participants will receive Rs 200. Which means the contributors will go home with Rs 200 each, while the non-contributors will go home with Rs 300 each. If the number of contributors falls short of six, nobody gets anything, so that the contributors lose their contribution, while the free riders get to keep their Rs 100. It is particularly interesting to observe if the response patterns change if you keep repeating the game time and again.
Mostly, such games are played with hypothetical money, so that the responses may or may not be similar to the responses that may be expected if the same game were played with real money. But games like these are often difficult to play with real money or, when played with real money, the amounts are typically too small to simulate realistic stakes. I have therefore played out this version of the experiment on several occasions substituting grade points for money when the participants were MBA students. You will be surprised how closely grade points mimic money. Like money, you prefer more grade points to less, you want more grade points than your neighbour, and you are willing to fight true and dirty to win more and more grade points.
In one session involving nineteen participants, when the same game was played five times, not even in one game did the number of contributors exceed six. The sheepish students repeatedly told me that while they really wanted to contribute, they ‘knew’ their colleagues ‘well enough’, so they chose to defect.
Typically in these games, any one individual is better off not contributing to the kitty, yet the group’s good is maximized only if a minimum number of individuals contribute. Researchers have experimented with the above version of the game in various situations. For example, participants in a game may or may not be allowed to talk to one another. Results indicate that often allowing people to talk to one another improves contribution, but does not eliminate non-contribution altogether.
In yet another variation, experiments have been conducted by splitting the participants into two groups, say,
of twelve individuals each. Exercises are conducted to ensure that each group develops its own identity. Then two clusters of twelve each are formed again, by drawing six members from each group. The same game is re-enacted and, in one of the clusters, the members are told that their kitty collections will go to six members of their original group playing within the cluster, while, in the second cluster, members are told that their kitty collections will go to their six colleagues from the original group, now playing in the other cluster. If people did not have group affiliations, one would expect no significant difference in free riding across these two groups. However, such is not usually the case, indicating that people tend to free ride less when they share a feeling of oneness with their associates. So perhaps, in a more patriotic people, the degree of free riding ought to be less.
An interesting portrayal of this phenomenon may be witnessed in our second-class unreserved train compartments. For instance, I would do everything possible to get into a compartment, and once I am in I would do everything possible to keep others out. Now, don’t we prove that hypothesis true in every walk of our life?
GREED, FEAR AND US
Why is it that, often, in these experiments the minimum threshold of contributors is not achieved? Clearly, the forces of greed and fear are at work here. Greed arises out of the possibility of taking home Rs 300 instead of Rs 200 should enough participants contribute. Fear arises out of the possibility that one may lose his Rs 100, if enough participants do not contribute. Which of the two sentiments is the more dominant?
We can modify the experiment to eliminate greed by ensuring that everyone (contributors as well as non-contributors) gets to take home Rs 200, provided a minimum of six guests contribute to the common kitty. Thus no one takes home Rs 300. Similarly, fear may be eliminated by providing for a ‘money-back guarantee’, where the contributors get their Rs 100 back in case the number of contributors falls short of six. However, should the number of contributors equal six or more, the contributors take home Rs 200 and the free riders Rs 300.
Researchers have found in these versions of the game that, in general, greed more than fear leads to free riding. For instance, Richard Thaler finds that while in the standard version the contributors averaged 51 per cent, in the no-fear version the contributors increased to 58 per cent, while in the no-greed version the contributors increased to 87 per cent. For corresponding Indian population, my limited and ad hoc experiments show these percentages to be around 30 per cent, 45 per cent and 85 per cent respectively.
Worldwide, in similar experiments, researchers have found 40 to 60 per cent of the respondents contributing to the kitty. For the Indian MBA student population, the percentage of contributors is closer to 35 per cent on an average. Could it be that, as a people, we Indians have a greater percentage of free riders? This is a hypothesis that needs rigorous testing.
SOME PRACTICAL IMPLICATIONS
From time to time, we hear of a company being bought out by employees or a portion of a company being restructured as an employee cooperative, with rewards based on the production of the unit. Leon Felkins says such arrangements do not always increase production dramatically.4 This is because each employee in such an arrangement finds himself in a ‘Commons’ situation with the usual reward for freeloading. Unless the free-riding phenomenon is controlled, production is more likely to go down than up. We see the same phenomenon in our larger housing cooperatives, where free riding abounds. Tenants routinely modify their apartments at will, refuse to pay maintenance charges and misuse the common facilities. As such cooperatives are not hierarchical in nature, when combined with our weak self-regulation, the incentive to free ride is high.
HOW MUCH DO WE FREE RIDE?
The enormous size of our bureaucracy and the concomitant anonymity offer the most conducive environment for free riding. No wonder we see a horde of government employees idling, knitting, chatting or free riding their time away in any number of government departments. What little work gets done in such departments is done by a very small minority of workers, and the overall efficiency and effectiveness of our governmental system remain abysmally poor.
A smaller, hierarchical organization probably reduces the extent of free riding in a system. It is not surprising then that in the smaller private-sector organizations we see relatively less free riding. The reasons are simple. In a vast governmental bureaucracy, the fear of being caught free riding is very low. Hence the greed to benefit as much as possible is very high. In a smaller, private organization, the reverse is true, and hence free riding is much less.
A large organization, even when hierarchical, is more or less flat at any given level as each level has a huge number of employees, thereby being more conducive for free riding. Typically, this is not the case with smaller private organizations.
FROM FREE RIDING TO CORRUPTION
From free riding to corruption is but one step. As the probability of discovery goes down and greed increases constantly, the tendency to free ride graduates to corruption. Little wonder we rank among the most corrupt countries in the world in most world surveys. Some estimates put the proportion of graft in government contracts between 30 and 40 per cent.
Corruption is so widespread in every aspect of the bureaucracy and so specialized that there is a whole book on the manipulation of transfers by Indian bureaucrats.5 The world-renowned Hoover Institution has an essay on India, ‘India: Asia’s Next Tiger?’ by Hilton L. Root on their website, which is indeed insightful: Root writes:
Where departments allocate licenses, subsidize goods, or raise money by black market sales (i.e., transport, public health, civil supplies, the development authority for land and projects), posts can command a good price. Power over postings, therefore, is a key to understanding corruption.
Of late there has been much excitement among the masses regarding the bold sting operations by some TV channels, exposing some government officials and politicians accepting bribes. But then, exceptions apart, being caught on the tape can hardly jeopardize one’s job or career, if one is resolute and can find someone else to bribe suitably.
Let us look at whether or not we are a systems-driven country and, if not, why?
CHAPTER 8
Systemic Chaos
India is a functioning anarchy. —J.K. Galbraith (US Ambassador to India, 1962)
WE NEITHER IMPLEMENT NOR FOLLOW SYSTEMS
We talked about our lack of self-regulation arising from our proclivity for large-scale defect–defect behaviour. This lack of self-regulation also, at least partially, explains why we are not a systems-oriented nation. As we all know, we can create practically anything; only we cannot maintain what we create. We build airports, sports complexes, cinema halls, roads, bridges, parks and what have you, only to let them all go to seed for lack of maintenance. We practically run the nation without established systems. In fact, it would appear that we are fundamentally incapable of respecting or following systems. One government, one chief minister, one chief executive, or one head of the department may create a certain system but, even before that system is implemented, it is changed by the successor. A change itself would not be bad provided the change were for the better, but our changes are more in the nature of arbitrary negation of the functioning system. It is as if we are afraid or reluctant to allow the predecessor’s systems work lest he gets the credit. In a way, our refusal to follow any system derives from our large-scale defection in the iterative PD situation.
ANATOMY OF SYSTEMS
No system can be foolproof. Every system of acceptance or rejection has two kinds of errors: Type 1 and Type 2. The first pertains to the possibility that an unworthy individual will pass muster in an examination or a defective product will pass quality control or a substandard service will be found acceptable. The second pertains to the likelihood that a worthy candidate will not make the grade or that a perfectly good product or service will be rejected. The best of systems cannot be foolproof against either kind of errors. They can only m
inimize them, unless one is willing to pay an enormous price.
If a system throws up one or the other error very often, clearly the system needs a review. But even when a system is fairly robust, one cannot rule out the two errors rising occasionally. The critical question is: When a system throws up an odd decision which suffers from one of the two errors, what should our course of action be? There are three options: a) In our belief that we have a sound system in place, we may accept that odd error as a one-off error, not warranting a change in the system per se; b) we may accept that particular decision, but look at ways to strengthening our system further so that such errors are further minimized in the future; or c) we may completely disregard the system and arbitrarily ‘correct’ the decision by reversing it, without doing anything to correct the system.
In case of ‘a’ or ‘b’, the integrity of a system that we believed to be fairly robust is respected. But what about alternative ‘c’? This course of action not only demoralizes or discredits the current system, it also destroys the foundation for any system at all and, what is more, it increases both kinds of errors in due course and hence amounts to a defect type of decision. This is exactly the course we most often pursue.
Games Indians Play Page 10
